Approved afforestation and reforestation baseline and ... · reforestation project activities under the control of the project participants. UNFCCC/CCNUCC CDM – Executive Board

UNFCCC/CCNUCC CDM – Executive Board AR-AM0007 / Version 03 Sectoral Scope: 14 EB 42

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Approved afforestation and reforestation baseline and monitoring methodology AR-AM0007

“Afforestation and Reforestation of Land Currently Under Agricultural or Pastoral Use”

Source

This methodology is based on the draft CDM-AR-PDD “Chocó-Manabí Corridor Reforestation and Conservation Carbon Project” whose baseline study, monitoring and verification plan and project design document were prepared by EcoSecurities Consult, Britain; Joanneum Research, Austria; Conservation International, USA; and EcoDecision. For more information regarding the proposal and its consideration by the Executive Board please refer to case ARNM0021-rev: “Chocó-Manabí Corridor Reforestation and Conservation Carbon Project” at: <http://cdm.unfccc.int/goto/Arpropmeth>.

Section I. Summary and applicability of the baseline and monitoring methodologies

1. Selected baseline approach from paragraph 22 of the CDM A/R modalities and procedures

“Existing or historical, as applicable, changes in carbon stocks in the carbon pools within the project boundary”

2. Applicability

This methodology is applicable to the following project activities:

• Afforestation or reforestation activities undertaken on pasture, agricultural land or abandoned lands; land use change is allowed in the baseline scenario.

The conditions under which this methodology is applicable to A/R CDM project activities are:

• Lands to be afforested or reforested are currently pasture or agricultural land or abandoned lands;

• Environmental conditions, human-caused degradation or ongoing human activities do not permit the spontaneous encroachment of natural forest vegetation;

• The application of the procedure for determining the baseline scenario in Section II.4 leads to the conclusion that the baseline approach 22(a) (existing or historical changes in carbon stocks in the carbon pools with the project boundary) is the most appropriate choice for determination of the baseline scenario;. This implies that only land uses that currently form part of the land use pattern within the analyzed area are plausible alternative land uses for the baseline scenario.

• Biomass of non-tree vegetation is in a steady state or decreasing for all baseline land uses; for rotational land-use systems, peak biomass over the rotation has to be constant or decreasing over several rotations;

• Lands will be afforested or reforested by direct planting and/or seeding;

• Site preparation does not cause significant longer-term net decreases of soil carbon stocks or increases of non-CO2 emissions from soil carbon. In particular, soil disturbance is insignificant, so that CO2 and non CO2-greenhouse gas emissions from these activities can be neglected. Soil drainage is not permitted;

• Flooding irrigation is not permitted;


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• Greenhouse gas emissions from denitrification due to the use of nitrogen-fixing species are not significant;

• Plantation may be harvested with either short or long rotation and will be regenerated either by direct planting, sowing, coppicing or assisted natural regeneration;

• For each of the alternative land uses being part of the baseline scenario, carbon stocks in soil-organic carbon can be expected to decrease more or increase less in the absence of the project activity, relative to the project scenario;

• All of the plausible land use changes being part of the baseline scenario shall lead only to such changes in soil organic carbon stocks that the stocks can be expected to decrease more or increase less, relative to afforestation/reforestation of the project area;

• Displacement of landowners that lose their farms due to the project activity is not expected to occur.

• Agricultural and pastoralpre-project activities shall be terminated on commencement of the A/R project activity and their shift outside of the project boundary is not expected to occur. The A/R CDM project activity shall not lead to destocking of existing forested areas in any ways other than possible farming undertaken by the displaced people (other than landowners of the project area) and farming or pastoral activities undertaken by the displaced people shall not lead to significant increase in non-CO2 emissions

The use of a Geographical Information System (GIS) platform and the use of Global Positioning System receivers are recommended.

3. Selected carbon pools:

Table 1: Selection and justification of carbon pools

Carbon pools Selected (answer with

Yes or No)

Justification / Explanation of choice

Above-ground Yes Major carbon pool subjected to the project activity Below-ground Yes Major carbon pool subjected to the project activity Deadwood Yes Major carbon pool subjected to the project activity Litter Yes Major carbon pool subjected to the project activity Soil organic carbon No Excluded. Conservative approach under applicability

conditions

4. Summary of baseline and monitoring methodologies

Baseline methodology steps

The baseline methodology is structured into the following steps:

Step 1: Demonstrate the applicability of the methodology to the specific project activity.

Step 2: The project boundary is defined for all discrete parcels of land to be subjected to afforestation or reforestation project activities under the control of the project participants.


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Step 3: The eligibility of land for an A/R CDM project activity is demonstrated by applying the latest version of the “Procedures to Demonstrate the Eligibility of Lands for Afforestation and Reforestation CDM Project Activities” as approved by the Executive Board.based on definitions provided in p33aragraph 1 of the annex to the decision 16/CMP.1 (“Land use, land-use change and forestry”), as requested by decision 5/CMP.1 (“Modalities and procedures for afforestation and reforestation project activities under the clean development mechanism in the first commitment period of the Kyoto Protocol”), until new procedures to demonstrate the eligibility of lands for afforestation and reforestation project activities under the clean development mechanism are approved by the Board

Step 4: Stratification of the A/R CDM project area is based on local site classification map/table, the most updated land-use/land-cover maps, satellite image, soil map, vegetation map, landform map as well as supplementary surveys, and the baseline land-use/land-cover is determined separately for each stratum.

(a) Sub-step 1. Stratification according to the baseline projections;

(b) Sub-step 2. Stratification according to the project scenario;

(c) Sub-step 3. Final ex ante stratification.

Step 5: This methodology applies approach 22(a), taking into account historical land use/cover changes, national, local and sectoral policies that influence land use within the boundary of the proposed A/R CDM project activity, economic attractiveness of the project relative to the baseline, and barriers for implementing project activities in absence of CDM finance. The baseline approach 22(a) is applied to extrapolate historical changes in carbon stocks in the carbon pools within the project boundary past land use change trends into the future over the crediting period.

The baseline scenario is determined by the following sub-steps:

(a) Identify and list plausible alternative land uses on the project lands;

(b) Map current and historical land use;

(c) Derive land-use change trends;

(d) Extrapolate the observed past trends into the future.

Step 6: Determination of baseline carbon stock changes, applying approach 22(a). The baseline carbon-stock changes are estimated based on the identified baseline land-use scenario (Step 5).

For strata without growing trees or woody perennials, this methodology assumes that the carbon stock in above- and below-ground biomass, as well as deadwood and litter would remain constant in the absence of the project activity, i.e., the baseline net GHG removals by sinks are assumed to be zero.

For strata with a few growing trees or woody perennials, the baseline net GHG removals by sinks are estimated based on the carbon stock changes in above- and below-ground biomass (in living trees), litter and deadwood.

To estimate carbon stock decreases due to land preparation for planting, this methodology conservatively estimates the highest carbon stock in above- and below-ground living biomass, as well as deadwood and litter that exists through the current land use cycle.

The loss of non-tree living biomass on the site due to competition from planted trees or site preparation is accounted as a carbon stock decrease within the project boundary, in a conservative manner.


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The omission of the soil organic matter can considered to be conservative if it can be justified that this pool would decrease more or increase less in the absence of the proposed A/R CDM project activity, relative to the project scenario. This assumption has to be demonstrated through pre-project measurements in representative pastures, agricultural lands and forest areas, or alternatively based on scientific literature.

Step 7: Ex ante actual net GHG removal by sinks are estimated for each type of stand to be created with the A/R CDM project activity. Stand types are represented by a description of the species planted or regenerated and the management prescribed (species, fertilization, thinning, harvesting, etc.). Carbon stock changes and the increase of GHG emissions resulting from fertilization, site preparation (biomass burning) and fossil fuel consumption are estimated using methods developed in IPCC GPG-LULUCF (IPCC 2003)1 and IPCC 1997).2

Step 8: This methodology uses the latest version of the “Tool for the demonstration and assessment of additionality for afforestation and reforestation CDM project activities” approved by the CDM Executive Board.3

Step 9: Leakage emissions, including carbon stock decreases outside the project boundary, are accounted for the following sources: fossil fuels consumption for transport of staff, products and services, displacement of the former employees on the lands leakage due to carbon stock decreases caused by displacement of pre-project grazing activities, and leakage from the increased use of wood posts for fencing and from the displacement of fuel-wood collection.

Monitoring methodology steps

This methodology includes the following elements:

Step 1: The overall performance of the proposed A/R CDM project activity is monitored, including the integrity of the project boundary and the success of forest establishment and forest management activities.

Step 2: Stratification of the project area is monitored periodically as the boundary of the strata may have to be adjusted to account for unexpected disturbances, changes in forest establishment and management, or because two different strata may become similar enough in terms of carbon to justify their merging.

Step 3: Baseline net GHG removals by sinks are not monitored in this methodology. The ex ante estimate is “frozen” on a per area-unit basis for the entire crediting period.

Step 4: The calculation of ex post actual net GHG removals by sinks is based on data obtained from permanent sample plots and methods developed in IPCC GPG-LULUCF to estimate carbon stock changes in the carbon pools and increase of project emissions due to fossil fuel consumption and nitrogen fertilization.

Step 5: Leakage due to vehicle use for transportation of staff, seedlings, timber and non-forest products, as a result of the implementation of the proposed A/R CDM project activities is monitored.

1 IPCC (2003): Good practice guidance for land use, land-use change and forestry. Institute for Global

Environmental Strategies (IGES), Hayama. 2 IPCC (1997): Revised 1996 IPCC guidelines for national greenhouse gas inventories; Volume 3: Greenhouse gas

inventory reference manual, <http://www.ipcc-nggip.iges.or.jp/public/gl/invs6.htm>. 3 Throughout this document, “A/R additionality tool” refers to the document approved by the Executive Board of the

CDM on the CDM website: <http://cdm.unfccc.int/Reference/tools>.


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Step 6: Leakage due to displacement of employees from the project area to other areas, carbon stock decreases caused by displacement of pre-project grazing activities, the increased use of wood posts for fencing and the displacement of fuel-wood collection outside the project boundary is monitored.

Step 7: A Quality Assurance/Quality Control plan, including field measurements, data collection verification, data entry and archiving, as an integral part of the monitoring plan of the proposed A/R CDM project activity, to ensure the integrity of data collected and improve the monitoring efficiency.

The baseline net GHG removals by sinks do not need to be measured and monitored over time. However, the methodology checks and re-assesses the baseline assumptions if a renewable crediting period is chosen.

This methodology uses permanent sample plots to monitor carbon stock changes in living tree biomass pools. The methodology first determines the number of plots needed in each stratum/sub-stratum to reach the targeted precision level of ±10% of the mean at the 95% confidence level. GPS is used to locate plots.


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Section II. Baseline methodology description

1. Project boundary

This methodology demonstrates eligibility of A/R CDM project activities based on definitions provided in paragraph 1 of the annex to the decision 16/CMP.1 (“Land use, land-use change and forestry”), as requested by decision 5/CMP.1 (“Modalities and procedures for afforestation and reforestation project activities under the clean development mechanism in the first commitment period of the Kyoto Protocol”), until new procedures to demonstrate the eligibility of lands for afforestation and reforestation project activities under the clean development mechanism are approved by the Board.

The “project boundary” geographically delineates the afforestation or reforestation project activity under the control of the project participants. The A/R CDM project activity may contain more than one discrete area of land. At the time the PDD is validated, the following shall be defined:

• Each discrete area of land shall have a unique geographical identification;

• The project participants shall describe legal title to the land, rights of access to the sequestered carbon, current land tenure, and land use for each discrete area of land;

• The project participants shall justify, that during the crediting period, each discrete area of land will be subject to an afforestation or reforestation project activity under the control of the project participants.

It shall be demonstrated that each discrete area of land to be included in the boundary is eligible for an A/R CDM project activity. Project participants shall apply the latest version of the “Procedures to Demonstrate the Eligibility of Lands for Afforestation and Reforestation CDM Project Activities” as approved by the Executive Board.

The sources and gases included in the project boundary are listed in Table 2 below.

Table 2: Emissions sources included in or excluded from the project boundary

Sources Gas Included Justification / Explanation of choice CO2 No Not applicable CH4 No Not applicable Use of fertilizers N2O Yes Main gas of this source CO2 Yes Main gas of this source CH4 No Potential emission is negligibly small

Combustion of fossil fuels e.g., on-site and/or offsite use of vehicles N2O No Potential emission is negligibly small

CO2 No However, carbon stock decreases due to burning are accounted as a carbon stock change

CH4 Yes Non-CO2 gas emitted from biomass burning Burning of biomass

N2O Yes Non-CO2 gas emitted from biomass burning


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2. Ex ante stratification

Stratification of the project area into relatively homogenous units will increase the accuracy of the estimation of baseline and actual carbon stock changes. In this methodology, stratification is achieved in three steps. Step 1 stratifies the project area according to pre-existing natural conditions and baseline projections in mBL strata; Step 2 stratifies the project area according to projected A/R CDM project activities in mPS strata; and Step 3 achieves the final ex ante stratification by combining the results of Step 1 with those of Step 2:4

Step 1: Stratification according to pre-existing conditions:

1. Define the factors influencing carbon stock changes, especially in above- and below-ground biomass pools. These factors may include soil, climate, previous land use, existing vegetation type, degree of anthropogenic pressure in the baseline scenario, etc.;

2. Collect local site classification maps/tables, the most updated land use/cover maps, satellite images, soil maps, vegetation maps, landform maps, and literature reviews of site information concerning key factors identified above;

3. Do a preliminary stratification based on the collected information;

4. Carry out supplementary sampling for site specifications for each stratum, including as appropriate:

(a) Area cover for herbaceous plants and crown cover, height and DBH for shrubs and trees (preferably species or cohort specific), respectively;

(b) Events that have resulted in deforestation, and their timing;

(c) Likely land use in the absence of an A/R CDM project activity;

(d) Present/potential vegetation types, alternatively, site and soil factors: soil type, soil depth, slope gradient, slope face, underground water level, etc.;

(e) Animal pressure, e.g. grazing.

5. Do the final stratification of the baseline scenario based on supplementary information collected from point 4 above. Distinct strata should differ significantly in terms of their baseline net greenhouse gas removals by sinks. For example, separate strata could consist of sites: totally deprived of trees or shrubs; with some trees or shrubs already present; subject to intensive collection of fuel wood or grazing. On the other hand, site and soil factors may not warrant a separate stratum as long as all lands have a baseline of continued degradation.

The stratification of the baseline scenario does not need to coincide with the areas that are covered by the various land-use types. One stratum can contain many different land-use types. On the other hand, one land-use type may occur in different strata, and different rates of land-use change may be observed in different strata. Therefore, when determining the baseline land-use scenario in the following sections, areas of the land-use types are tracked stratum by stratum.

4 Baseline and actual net GHG removal by sinks are expected to be significantly different. Accordingly, different

stratifications may be required for the baseline scenario (Step 1) and for the project scenario (Step 2) to achieve optimal accuracy of the estimates of net GHG removal by sinks.


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Step 2: Stratification according to the planned A/R CDM project activity:

1. Define the project scenario to be implemented in the project area by specifying:

(a) The species or species combination to be planted together in one single location and at the same date to create a “stand”;

(b) The growths assumptions for each species, combination of species in the stand type;

(c) Planting, fertilization, thinning, harvesting, coppicing, and replanting cycle scheduled for each stand type, by specifying:

• The age class when the above management activities will be implemented;

• The quantities and types of fertilizers to be applied;

• The volumes to be thinned or harvested;

• The volumes to be left on site (harvest residues becoming deadwood) or extracted.

2. Define the establishment timing of each stand by specifying:

(a) The planting date;

(b) The area to be planted (ha);

(c) The geographical location for each stand.

3. Stratify the project area according to the above specifications. Distinct strata should differ significantly from each other in terms of their actual net greenhouse gas removals by sinks. On the other hand, species and management (thinning, harvesting and replanting) and other factors of the project scenario may not warrant a separate stratum as long as all lands have similar actual stock changes in the carbon pools.

Step 3: Final ex ante stratification:

1. Verifiably delineate the boundary of each stratum as defined in Steps 1 and 2 using GPS, analysis of geo-referenced spatial data, or other appropriate techniques. Check consistency with the overall project boundary. Coordinates may be obtained from GPS field surveys and/or analysis of geo-referenced spatial data, including remotely sensed images, using a Geographical Information System (GIS);

2. Preferably, project participants shall build geo-referenced spatial data bases in a GIS platform for each parameter used for stratification of the project area under the baseline and the project scenario. This will facilitate consistency with the project boundary, precise overlay of baseline and project scenario strata, transparent monitoring and ex post stratification.

Note: In the equations used in this methodology, the letter i is used to represent a stratum and the letter m for the total number of strata. mBL is the number of ex ante defined baseline strata as determined with Step 1; mBL remains fixed for the entire crediting period. mPS is the number of strata in the project scenario as determined ex ante with Step 2. Ex post adjustments of the strata in the project scenario (ex post stratification) may be needed if unexpected disturbances occur during the crediting period (e.g. due to fire, pests or disease outbreaks), affecting differently different parts of an originally homogeneous stratum or stand, or when forest management (planting, thinning, harvesting, replanting) occurs at different intensities, dates and spatial locations than originally planned.


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3. Procedure for selection of most plausible baseline scenario

Summary explanation of the approach

This methodology allows setting a baseline land-use scenario according to approach 22(a) as the continuation of past land-use change trends. If past trends are assumed to continue and if these past trends entailed land-use change, then the baseline scenario will also show the expected land-use change. This methodology therefore provides a procedure for quantifying past land-use change trends. It also provides a procedure for extrapolating these past land-use change trends into the future.

This methodology quantifies the annual land-use change as an area that a land-use type changes by. Land-use change trends are quantified as “hectares changing, per year” of a given land-use type. The area-based approach is linear, and conceptually straightforward, given that commonly land-use data are only available for a limited number (two) of discrete points in time (two satellite images). This methodology, therefore, opts for the linear, area-based approach in identification past land-use change trends and extrapolating them into the future.

This section identifies land-use changes by tracking the areas of land-use types. Baseline GHG removals by sinks are then determined as a function of land-use changes between years.Step-by-step description of the approach

Project participants shall determine the most plausible baseline scenario for each of the identified ex ante strata with the Steps 1-7 described below.

In line with applicability condition 3, this methodology is not applicable if project proponents can not clearly show in the application of Steps 1 to 8 that, the baseline approach 22(a) (existing or historical changes in carbon stocks in the carbon pools with the project boundary) is the most appropriate plausible baseline scenario.

The following procedure determines the baseline land use on a stratum-by-stratum basis. If it is possible to broaden the analysis to a representative vicinity of the project area, i.e. if the land-use drivers in this representative vicinity are representative for the project area and its baseline strata, then this should be done. Consistently with the distinction between different strata, the representative vicinity of a stratum is defined by the baseline-stratification criteria (see step 1 in section II.2). The reference area for the determination of baseline land-use changes in a stratum shall be determined as follows:

(a) All areas of a stratum shall be considered that fall within the project boundaries.

(b) Additional areas in the project vicinity shall be considered that fall outside the project boundaries if these are representative for the stratum within the project area. For this purpose the project vicinity comprises all areas that fall inside a buffer zone of 5 km from the project boundaries for all discrete areas of land.

To ensure transparency all information used in the analysis and demonstration shall be archived and verifiable.


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Step 1: Identify and list plausible alternative land uses on the project lands for all strata

Considering relevant national and/or sectoral land-use policies that would impact the proposed project area and/or, if applicable, broader geographical area with similar socio-economic and ecological conditions, project participants shall identify realistic and credible Plausible alternative land uses. including alternative future public or private activities on the project lands. This shall include any similar A/R activity not undertaken not as CDM activity orand possibly any other feasible land development activities., considering relevant national and/or sectoral land-use policies that would impact the proposed project area and/or, if applicable, its representative vicinity. This should be carried out using selected available sources of data, including as appropriate archives, maps and/or satellite images, as well as supplementary field investigation, land-owner interviews, and/or other appropriate sources.

For identifying the realistic and credible land uses; remote sensing data, land use records, field surveys, data and feedback from stakeholders, and information from other appropriate sources, including Participatory rural appraisal (PRA)5 may be used as appropriate. All land uses within the boundary of the proposed A/R CDM project activity scenarios that are currently existing or that existed at some time since 31 December 1989 but no longer exist, may be deemed realistic and credible. For all other alternative land uses, credibility shall be justified. The justification shall include elements of spatial planning information (if applicable) or legal requirements and may include assessment of economical feasibility of the proposed alternative land use scenario.

The justification as mentioned above should lead to the conclusion that only land uses that currently exist or that existed at some time since 31 December 1989 but no longer exist, may be deemed realistic and credible as the methodology applies the 22(a) baseline approach.In line with applicability condition 3, this analysis should demonstrate that only land uses that currently form part of the land use pattern within the analyzed area are plausible alternative land uses for the baseline scenario. If any other land uses (e.g. land uses that would be (re-)introduced) are identified as plausible alternatives, this methodology is not applicable.

In the case of rotational land-use systems (such as shifting cultivation and fallow agriculture systems), all phases of such systems shall be grouped in only one land-use class, and they shall not be treated separately. The later derivation of the baseline carbon stocks treats those land-use types with cyclical management in an appropriate manner when considering the carbon releases and uptakes upon land-use change to correspond to the average carbon stock over the rotational cycle.6 It shall be substantiated that the vegetation does not meet the country’s forestry definition even at the most advanced phase of the cyclical land-use system hence; the A/R activities over the project lands are eligible A/R CDM project activities. as demonstrated based on definitions provided in paragraph 1 of the annex to the decision 16/CMP.1 (“Land use, land-use change and forestry”), as requested by decision 5/CMP.1 (“Modalities and procedures for afforestation and reforestation project activities under the clean development mechanism in the first commitment period of the Kyoto Protocol”), until new procedures to demonstrate 5 Participatory rural appraisal (PRA) is an approach to the analysis of local problems and the formulation of tentative

solutions with local stakeholders. It makes use of a wide range of visualisation methods for group-based analysis to deal with spatial and temporal aspects of social and environmental problems. This methodology approach is, for example, described in: Chambers R (1992): Rural Appraisal: Rapid, Relaxed, and Participatory. Discussion Paper 311, Institute of Development Studies, Sussex. and Theis J, Grady H (1991): Participatory rapid appraisal for community development. Save the Children Fund, London.

6 It is important that the carbon-stock estimates for the cyclical land-use systems correspond to the average carbon stock that these systems typically contain across the land-use cycle. One way of determining the average is to carry out a land-use inventory before project start that estimates the average carbon stock in those systems for the time point of the inventory and disregarding the phases. If the land-use sample is representative for the phases of the land-use cycle, the resulting average carbon stock will correspond to the average across the rotation cycle.


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the eligibility of lands for afforestation and reforestation project activities under the clean development mechanism are approved by the Board.

The level of detail to which age classes of land-use types need to be distinguished depends on the carbon stocks of those land-use types.

(a) In all land uses without woody perennials (e.g., grazing land, cropland), it is not necessary to account for the age of the possibly present other vegetation;

(b) In all land uses that contain woody perennials (e.g., regeneration, reforestation, coffee plantations, oil-palm plantations, agroforestry systems, etc.), age of the vegetation shall be accounted for;

(c) The phases of rotational land-use systems (such as shifting cultivation and fallow agriculture systems) shall be treated as one vegetation class and shall not be distinguished as to where they are in the cycle. The later derivation of the baseline removals treats those land-use types with various cyclical phases with an average carbon stock over the entire rotational cycle.

Step 2: Map current and historical land use at least for two reference dates for all strata

The land uses in the project region area and (if applicable) broader geographical area with similar socio-economic and ecological conditions its representative vicinity shall be mapped for two reference dates, i.e. start and end of the reference period (Tref). The classification legend for land-use mapping shall correspond to the alternative land uses identified in step 1. An analysis of land-use changes between these dates shall be carried out. This multi-temporal analysis of satellite images will later be used for the identification of land-use change trends (step 3). In order to ensure rigor in the identification of land-use change trends, this methodology has detailed provisions for the selecting of reference dates and the reference area. As appropriate, the project proponents may complement satellite images with other data sources, including as appropriate archives, maps of land use/cover, as well as supplementary field investigation, land owner interviews, and/or other appropriate sources, if necessary.

In selecting the reference dates period, the project proponents shall may consider use satellite images from dates that can also be used for demonstrating eligibility of lands. (if possible). The following provisions shall be followed:

(a) For the start of the reference period, the project proponents shall consider a date that is (if possible) earlier than and as close as feasible to the 31 December 1989. For the end of the reference period, the project proponents shall consider for the earlier image and a date that is reasonably close to the project start for the later image;

It is possible to have the start of the reference period base the multi-temporal analysis on a later date later than 31 December 1989 if land-use trends in the past were not representative subjected to different impacts than for the current land-use trends. during the entire period since 1990. In this case, the project proponents shall substantiate that using the later date leads to the identification of a representative land-use trend that is in line with the current impacts.

(b) In selecting the reference area, the project proponents shall follow the above provisions as to the representative vicinities of strata.


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Step 3: Represent land-use change through tabular forms for each of the strata in project area and/or the broader geographical area with similar socio-economic and ecological conditions. representative vicinities

Project proponents shall derive land-use change tabular representations from the multi-temporal analysis of land use based on data on area of each historical land use that changed into each current land use between the two reference dates within the reference period.

The land-use change data shall list areas (in ha) for each stratum and/or the broader geographical area with similar socio-economic and ecological conditions its representative vicinity in the following tabular way:

Table 3: Land-use change tabular representation of a stratum in the project area and/or its representative vicinity the broader geographical area with similar socio-economic and ecological conditions, if necessary.

[Name of the stratum]

[Later End year of the reference period] [Earlier Start year of the reference period] [LU#1] [LU#2] [LU#n] Sum

[LU#1]

[Area where LU#1 remains during the reference period]

[Area converted from LU#1 to LU#2 during the reference period]

[Area converted from LU#1 to LU#n during the reference period]

[Total area of LU#1 at the start in the earlier year of the reference period]

[LU#2]

[Area converted from LU#2 to LU#1 during the reference period]

[Area where LU#2 remains during the reference period]

[Area converted from LU#2 to LU#n during the referenceperiod]

[Total area of LU#2 at the start in the earlier year of the reference period]

[LU#n]1

[Area converted from LU#n to LU#1 during the reference period]

[Area converted from LU#n to LU#2 during the reference period]

[Area where LU#n remains during the reference period]

[Total area of LU#n at the start in the earlier year of the reference period]

Sum

[Total area of LU#1 in the later end yearof the reference period]

[Total area of LU#2 in the later year end of the reference period]

[Total area of LU#n in the later year end of the reference period] [Overall total area]

1 LU#n is name of the n-th land use in a stratum n

As the land-use change tabular representations identified in Step 3 may represent the past land-use changes in the broader geographical area with similar socio-economic and ecological conditions, stratum’s representative vicinity, they may also contain deforestation. In order to be conservative, the past land-use changes corresponding to deforestation shall be nullified. This is achieved by deleting the row representing forest land use in Table 3.

Note: The column representing forest land use shall be kept in order to represent possible reforestation/afforestation.


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Step 4: Plausibility check and correction for singular events

The land-use change tabular representation indicates the way of change of land uses. Under this step it is checked if these trends are biased by possible singular events. It may happen that a singular land-use change event occurred during the reference period and is not likely to be repeated in the future. The observed past land-use changes shall therefore be subjected to a plausibility-check in order to avoid bias from singular events. If a land-use change event can be considered singular, the land-use change tabular representation for the larger vicinity of the project area (step 3) shall be corrected.

Project proponents shall perform a plausibility-check of the land-use change. For each land use change observed during the reference period (e.g., the conversion of pastures into secondary forests), it shall be demonstrated for the observed area changes for each land use individually between the two reference dates (e.g., the conversion of pastures into secondary forests) that the most plausible baseline scenario is either of the following two:

• Continuation of the identified historical area change during the crediting period in absence of the project activity; or

• Continuation of the previous land-use type, and the change observed in the past is not likely to repeat considering relevant national and/or sectoral land-use policies. This shall be done by demonstrating that considering relevant national and/or sectoral land-use policies either the past land-use change trend for the respective land use does not apply is not likely to be continued any longer (e.g. it was caused by impacts that ceased to exist). , or that the land-use change was not part of any trend, but an isolated, singular event.

If the continuation of the current land use (rather than the continuation of the past change trend) is identified as the most plausible baseline scenario, the land-use change tabular representation shall be adjusted. The adjustment shall allow continuation of the respective land-use type. Correspondingly, the areas contained in some cells of the land-use change tabular representation need to be moved to its diagonal. For instance, if the land-use change from LU#1 to LU#2 was identified as a singular event then the corresponding area needs to be moved to the cell that expresses remaining area of LU#1 (i.e. diagonal - see Table 4). Table 4: Adjustment of the land-use change tabular representation by excluding singular past events of the stratum and its representative vicinity (in the grey cells)


[Later year] [Earlier year] [LU#1] [LU#2] [LU#n] Sum

[LU#1]

[Area where LU#1 remains] + [area converted from LU#1 to LU#2 as a result of singular event] 1 0 2

[Area converted from LU#1 to LU#n]

[Total area of LU#1 in the earlier year]

[LU#2] [Area converted from LU#2 to LU#1] [Area where LU#2 remains] [Area converted from LU#2 to LU#n]

[Total area of LU#2 in the earlier year]

[LU#n] [Area converted from LU#n to LU#1] [Area converted from LU#n to LU#2]

[Area where LU#n remains]

[Total area of LU#n in the earlier year]

Sum [Total area of LU#1 in the later year] [Total area of LU#2 in the later year]

[Total area of LU#n in the later year] [Overall total area]

1 The areas in this cell on the diagonal have been increased in order to correct for singular events. 2 This must be zero in consequence of the correction, because the areas that used to be in this cell were moved to the next cell to diagonal. The land use change from LU#1 to LU#2 was a result of singular event.


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Step 5: Derive land-use change trends using the land-use change tabular representation for each stratum

The following sub-steps shall be applied to the land-use change tabular representation of each stratum:

Sub-step 5.1: Derive per-ha and per-year relative land use changes for each entry

The land-use change tabular representation shall be transformed to list of relative valuesper area unit and per year. In order to do so, the cells in each row of in the above tabular representation that show area changes need to be divided by the duration of the reference period and by the total area covered by the respective land-use type at the start of the reference period.

For instance, over a reference period of 15 years croplands were converted into grazing lands on an area of 15 ha, while 85 ha of croplands remained unchanged. Since, the total area of croplands amounted to 100 ha before the change, the conversion needs to be quantified as 15 ha of change per 100 ha of existing croplands. The annual change of cropland into grazing land then amounts to 1 ha change / yr / 100 ha cropland.

The results shall be presented in the following manner:

Table 4: Observed relative Land land-use changes (per ha and per year) of in the each stratum in the project area and the broader geographical area with similar socio-economic and ecological conditions during the reference period (Tref) representative vicinity (unit of the entries: yr-1)

[name of the stratum] [LU#1] [LU#2] [LU#n]

[LU#1]

[Area that remained under LU#1 during the reference period] / [total area of LU#1 at the start of the reference period]-1= LC(1, 1)

[Area converted from LU#1 to LU#2 during the reference period] / ([later year] – [earlier year]) / [total area of LU#1 at the start in the earlier year of the reference period] = LC(1, 2)

[Area converted from LU#1 to LU#n during the reference period] / ([later year] – [earlier year]) / [total area of LU#1 at the start in the earlier year of the reference period] = LC(1, n)

[LU#2]

[Area converted from LU#2 to LU#1 during the reference period] / ([later year] – [earlier year]) / [total area of LU#2 at the start in the earlier year of the reference period] = LC(2, 1)

[Area that remained under LU#2 during the reference period] / [total area of LU#2 at the start of the reference period]-1 = LC(2, 2)

[Area converted from LU#2 to LU#n during the reference period] / ([later year] – [earlier year]) / [total area of LU#2 at the start in the earlier year of the reference period] = LC(2, n)

[LU#n]

[Area converted from LU#n to LU#1 during the reference period] / ([later year] – [earlier year]) / [total area of LU#n at the start in the earlier year of the reference period] = LC(n, 1)

[Area converted from LU#n to LU#2 during the reference period] / ([later year] – [earlier year]) / [total area of LU#n at the start in the earlier year of the reference period] = LC(n, 2)

[Area that remained under LU#n during the reference period] / [total area of LU#n at the start of the reference period]-1= LC(n, n)

1 These cells is empty, because this table only tracks changes and not unchanged areas.


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Sub-step 5.2: Determine starting land use for the project area

For each stratum inside the project boundary at project start, list the areas covered by the land uses. inside the stratum, inside the project boundary at project start. This will be the starting land use situation to extrapolate future define the baseline land use from.

List the areas of the land-use types in the stratum at the project start in the following way:

Table 5: Pre-project land use in a stratum at project start (unit of the entries: ha)

[Name of the stratum i] [LU#1] [Total Pre-project stratum area LU#1]

[LU#2] [Total Pre-project stratum area LU#2] [LU#n] [Total Pre-project stratum area LU#n] Sum [Total stratum initial area of the stratum i in the project]

Sub-step 5.3: Calculate the expected baseline Relate the land-use changes over a future (after project start) periods of duration equal to Tref tabular representation from the larger vicinity to the project area for each stratum in the project area

The justification mentioned in the Step 1 above has lead to the conclusion that only land uses that currently exist or that existed at some time since 31 December 1989 or during the reference period (Tref) but no longer exist, may be deemed realistic and credible. Therefore, In order to relate the trends observed for a larger area to the smaller project area, the results of sub-step 5.1 and sub-step 5.2 shall be combined. The per-ha and per-year changes from the stratum and its representative vicinity shall be multiplied with the stratum’s starting land use in order to derive the stratum’s per-year changes. the results reflect the expected baseline land-use the annual changes to be expected for the each stratum shall be calculated in the way presented in the Table 6. The results shall be presented in the following way:

Table 6: Baseline land-use changes (per-year) for the each stratum in the project area changes over a future (after project start) periods of duration equal to Tref (NHO:The language should be revised along the lines Baseline land use changes for each stratum in the project area calculated in time steps equal in duration for number of years after project start equal to those into the reference period Tref (unit of the entries: ha * yr-1)

[Name of the stratum] [LU#1] [LU#2] [LU#n] Sum

[LU#1]

LC(1, 1)-1* [Project stratum area LU#1 in the intial year of the period]

LC(1, 2) [Area converted from LU#1 to LU#2] / ([later year] – [earlier year]) / [total area of LU#1 in the earlier year] * [Project total stratum area LU#1 in the intial year of the period]

LC(1, n)[Area converted from LU#1 to LU#n] / ([later year] – [earlier year]) / [total area of LU#1 in the earlier year * [Project total stratum area LU#1 in the intial year of the period]

[Project stratum area decreases LU#1 in the intial year of the period]


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[Name of the stratum] [LU#1] [LU#2] [LU#n] Sum

[LU#2]

LC(2, 1) [Area converted from LU#2 to LU#1] / ([later year] – [earlier year]) / [total area of LU#2 in the earlier year] * [Project total stratum area LU#2 in the intial year of the period]

LC(2, 2)* [Project stratum area LU#2 in the intial year of the period-1

LC(2, n) [Area converted from LU#2 to LU#n] / ([later year] – [earlier year]) / [total area of LU#2 in the earlier year] * [Project total stratum area LU#2 in the intial year of the period]

[Project stratum area decreases LU#2 in the intial year of the period]

[LU#n]

LC(n, 1) [Area converted from LU#n to LU#1] / ([later year] – [earlier year]) / [total area of LU#n in the earlier year] * [Project totalstratum area LU#n in the intial year of the period]

LC(n, 2) [Area converted from LU#n to LU#2] / ([later year] – [earlier year]) / [total area of LU#n in the earlier year] * [Project total stratum area LU#n in the intial year of the period]

LC(n, n) * [Project stratum area LU#n in the intial year of the period-1

[Project stratum area decreases LU#n in the intial year of the period]

Sum

[Project stratum areaincreases LU#1 in the final year of the period]

[Project stratum area increases LU#2 in the final year of the period]

[Project stratum area increases LU#n in the final year of the period]

1 These cells must be empty, because this table only tracks changes and not unchanged areas.

The calculations presented in the Table 6 shall be repeated k times until k*Tref is equal to, or greater than the duration of the crediting period selected by PPs. For each repetition [Project stratum area LU#n in the final year of the period] calculated in the previous step, shall be entered as the respective [Project stratum area LU#n in the intial year of the period] in the next step of the calculation.

The outcome of this step is presented in Table 7 (below):

Table 7: Land uses in a stratum i at different moments t (unit of the entries: ha)

[Name of the stratum i] Project start t=Tref t=2*Tref t=k*Tref

[LU#1] [Pre-project stratum area LU#1]

[Project stratum area LU#1] at t=Tref

[Pre-project stratum area LU#1] at t=2*Tref

[Pre-project stratum area LU#1] at t=k*Tref

[LU#2] [Pre-project stratum area LU#2]

[Project stratum area LU#2] at t=Tref

[Pre-project stratum area LU#2] at t=2*Tref

[Pre-project stratum area LU#2] at t=k*Tref

[LU#n] [Pre-project stratum area LU#n]

[Project stratum area LU#n] at t=Tref

[Pre-project stratum area LU#n] at t=2*Tref

[Pre-project stratum area LU#n] at t=k*Tref

Sum

[Total initial area of the stratum i in the project]

[Total area of the stratum i in the project] at t=Tref

[Total area of the stratum i in the project] at t=2*Tref

[Total area of the stratum i in the project] at t=k*Tref

Sub-step 5.4: Derive the annual land-use change trends for the stratum

The annual land-use change trends by land-use type for the stratum shall be derived as the difference between increases and decreases as derived in sub-step 5.3. The annual change trends shall be presented in the following way:


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Table 8: Annual baseline land-use change trends for the stratum (unit of the entries: ha * yr-1)


[LU#1] [LU#1 net change] = [stratum area increases LU#1] – [stratum area decreases LU#1]

[LU#2] [LU#2 net change] = [stratum area increases LU#2] – [stratum area decreases LU#2]

[LU#n] [LU#n net change] = [stratum area increases LU#n] – [stratum area decreases LU#n]

Sum 0

Step 6: Extrapolate Interpolation of the observed past trends land use changes into the future for each stratum The area of all land uses in each stratum in each year of the crediting period shall be calculated by interpolating the projected land use changes from Sub-step 5.3. The following steps shall be applied:

Sub-step 6.1: Calculate the annual land-use changes for each stratum

For each period equal to Tref, the annual net land-use change by land-use type for each stratum shall be calculated as the difference between the area of each land use in the stratum at final year and the initial year of the respective period divided by the duration of the reference period.

[LU#n annual net change] = ([Project stratum area LU#n in the final year of the period] – [Project stratum area LU#n in the intial year of the period])/Tref

Sub-step 6.2: Interpolate the annual areas subjected to different land-uses in each stratum

The area of all land uses in each stratum in each year of the crediting period shall be calculated in the following way:

The most plausible baseline scenario shall be identified by extrapolating the historical area change trends in land use identified in Step 5 above into the future. For the first period (equal to Tref ) following project implementation:

[Project stratum area LU#n in the year t=tx] = [Pre-project stratum area LU#n]+[LU#n annual net change for the first period]*tx

For the second period (equal to Tref ) following project implementation:

[Project stratum area LU#n in the year t=tx] = [Project stratum area LU#n] at t=Tref + [LU#n annual net change for the second period]*(tx-Tref)

For the k-th period (equal to Tref ) following project implementation:

[Project stratum area LU#n in the year t=tx] = [Project stratum area LU#n] at t=(k-1)*Tref + [LU#n annual net change for the k-th period]*(tx-(k-1)*Tref)

The calculations will stop when tx equals the length of the crediting period.

For each year of the crediting period, the project proponents shall assign an expected area to each of the land-use types that are part of the baseline (identified in Step 1).


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The following procedure shall be applied for extrapolating past land-use change trends as identified in step 5 into the future:

(a) The baseline land use in year 1 corresponds to the pre-project land use (sub-step 5.2).

(b) The baseline area that a land-use type covers in any subsequent year corresponds to the sum of the area covered by the land-use type in the previous year and annual baseline land-use change trend for the stratum (read from the Table 7). For instance, the baseline area that a land-use type covers in year 2 corresponds to the sum of the area covered by the land-use type in the pre-project land use situation (sub-step 5.2) and the area by which the respective land use is expected to change (sub-step 5.4).

The baseline land-use scenario shall be presented for each stratum i by specifying the areas Aijt that all land uses j cover in each year tx using Table 8:

Table 8: Extrapolated Interpolated areas of baseline land-uses changes (per-year) for the stratum i (unit of the entries: ha)

[Name of the stratum i]

Land use j = [LU#1] Land use j = [LU#2] Land use j = [LU#n] Sum

Year t=1

Ai j=1 t=1 = area covered by land use 1 in stratum i in year 1


Ai j=n t=1 = area covered by land use n in stratum i in year 1 [Total stratum area]

Year t=2



Ai j=n t=2 = area covered by land use n in stratum i in year 2 [Total stratum area]

Year t=tx

Ai j=1 t=tx = area covered by land use 1 in stratum i in year tx

Ai j=2 t=tx = area covered by land use 2 in stratum i in year tx

Ai j=n t=tx = area covered by land use n in stratum i in year tx [Total stratum area]

Step 7 (if necessary): Guidance on how to treat cessation of land uses within the project duration as a result of extrapolating land use changes

While extrapolating negative net annual changes for a land use type, this land use type could cease to exist within the project duration. In this case, the land use change trend cannot be extrapolated beyond the time at which the land use area reaches zero. The year, in which one (or more) of the areas of all land uses reach(es) zero, can be determined by the following procedure for land use LU#n:

• if [LU#n net annual change] = [stratum area increases LU#n] – [stratum area decreases LU#n] < 0, and

• if [initial area LU#n] / [LU#n net annual change] < project duration

then, the year tx, = [initial area [LU#n]] / [LU#n net annual change]

where:

tx Year in which the area of a land use reaches zero within the project duration

For the extrapolation following this year, the following steps need to be carried out instead of further applying the land-use change trend:


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(a) In Table 6 in sub-step 5.3 all land-use changes shall be eliminated that involve the land-use type, the area of which reaches 0. For instance, if for certain tx the area of land-use type LU#2 becomes 0, then for each t>tx all land-use changes of LU#2 into other land-use types shall be 0, as well as all land-use changes of other land-use types into LU#2 shall be 0. That is, all cells in the respective row and the respective column of Table 6 shall be zeroes.

(b) Repeat sub-step 5.4 with the updated land-use changes and derive the adjusted net-annual land-use change trends for the stratum.

(c) Continue applying step 6 with the updated annual land-use change trends.

For the determination of further land uses ceasing to exist while applying the updated annual land-use change trends, the reference period for the calculations outlined below is the time span between the year the last land use ceased to exist and the end of the project:

• if [updated LU#n net annual change] = [updated stratum area increases LU#n] – [updated stratum area decreases LU#n] < 0, and

• if [area LU#n at the year the last land use ceased to exist] / [updated LU#n net annual change] < project duration – years since the start of the project until the year the last land use ceased to exist

then, the year tx, in which the next area of a land use reaches zero within project duration equals [area LU#n at the year the last land use ceased to exist] / [updated LU#n net annual change]

If further land uses cease to exist, the same procedure applies as outlined above.

Step 7: Estimate baseline net GHG removals by sinks from the baseline scenario for each stratum

The application of Steps 1-67 results in a yearly record of areas that all baseline land uses cover for each year of the crediting period in each stratum. The following section uses this early record to establish the baseline net GHG removals by sinks.

4. Additionality

This methodology uses the latest version of the “Tool for the demonstration and assessment of additionality for afforestation and reforestation CDM project activities” approved by the CDM Executive Board.7

When applying the additionality tool, the project proponents shall consider applicability conditions and include the justification required in Annex 19, EB 24:

• In demonstrating the additionality of the project, it needs to be taken into account that the baseline could also include afforestation and reforestation. According to the provisions of Annex 19 to the report from the 24th meeting of the Executive Board, “the assessment of additionality shall include justification that the increased rate of afforestation/reforestation would not occur in the absence of the project activity and results from direct intervention by project participants”.

In line with applicability condition 3, only land uses that currently form part of the land use pattern within the analyzed area are plausible alternative land uses for the baseline scenario. If any other land uses (e.g. land uses that would be (re-)introduced) are identified as plausible alternatives this methodology is not applicable.

7 Hereinafter referred as “A/R additionality tool”. Please refer to <http://cdm.unfccc.int/Reference/tools>.http://cdm.unfccc.int/goto/Arappmeth


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5. Estimation of baseline net GHG removals by sinks

5.1. Summary explanation of the approach

This methodology allows for land-use change in the baseline scenario. The dynamic baseline scenario with respect to the areas that land-use types cover over the crediting period (described in Section 3) requires a particular way of tracking carbon stock changes that remaining and changing land-use changes entail (described in this section).

This methodology quantifies for each land-use type within a stratum (and year-by-year) the areas that continue to be covered by the respective land-use type. It also quantifies area changes: land-use types can either increase or decrease. Most other methodologies do not account for land-use change; therefore they only deal with areas that continue to be covered by the respective land-use types.

For areas that remain, i.e., that continue to be covered by the same land-use type, the same approach as in most other methodologies is applied. If the areas have woody perennials, carbon stock changes are estimated as a function of their growth rates. Alternatively, if the areas do not have woody perennials, it is assumed that carbon-stocks remain constant.

For areas that undergo land-use change, i.e. where the area of a land-use type increases or decreases, a new approach is proposed. Land-use change is considered as increases and decreases of areas covered by the respective land-use types. For instance, the change of sugar cane to pasture is considered a decrease of sugar cane together with an increase of pasture.

Looking at the sum of decreases and increases for determining carbon stock changes from land-use change is mathematically equivalent to the difference of carbon stocks before and after the change. For instance, the change of sugar cane (8 t C per ha) to pasture (5 t C per ha) will lead to a carbon stock change of -3 t C per ha. It is mathematically equivalent to calculate:

[carbon stock after the change, i.e., 5 t C per ha] – [carbon stock before the change, i.e. 8 t C per ha],

or to calculate:

[carbon stock decrease from decreasing area of sugar cane, i.e. -8 t C per ha] + [carbon stock increase from increasing area of pasture, i.e. +5 t C per ha].

The methodology assigns carbon stock changes to the decreases and increases of areas of land-use types. The carbon stock changes from land-use change are assigned in a conservative manner, as the methodology prescribes that when areas of land-use types increase the carbon-stocks are overestimated, and when areas of land-use types decrease the carbon-stocks are underestimated.


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5.2. Step-by-step description of the approach

To determine the baseline net GHG removals by sinks, the following steps are necessary to be carried out for every year of the crediting period and for each stratum of the project area:

(1) Determination of the areas that each land-use type will cover following the procedures outlined in Section II.2 and II.3. This step results in the table Table listed in step 5 of section II.3.

(2) Determine the areas of the land-use types expected to remain and expected to change.

(a) Determine the area of each land-use type that is expected to remain unchanged between two given years. Following the notation in the table listed in Step 5 of Section II.3, the area of a land-use type j=LU#n expected to remain between a given year t=tx and the subsequent year t=tx+1 is denoted as ARemain i j=n t=tx. The area of each land-use type that is expected to remain corresponds to the smaller area of those that the land-use types cover before and after the change;

ARemain i j=n t=tx = min { Ai j=n t=tx, Ai j=n t=tx+1 } (B.1)

where:

ARemain i j=n t=tx Area of the species (= land-use type) j 8 that is expected to remain, in stratum i, between year tx and tx+1; ha

tx Starting year of a land-use change; year

Aijt Area of stratum i, species (= land-use type) j, at time tx; ha

Note: The use of the minimum function is an easy way of determining areas that do not undergo changes between two years. For instance, if a land-use type has 8 ha in year 1 and 13 ha in year 2, then the lesser (namely 8 ha), correspond to the areas that remained without change between the years.

(b) Determine the area of each land-use type that is expected to change between two given years. This analysis does not track changes between land-use types, but is limited to increases in areas and decreases in areas. The sum of all changes for all land-use types must be 0 for each year. Following the notation in the table listed in Step 5 of Section II.3, the area of a land-use type j=LU#n expected to change between a given year t=tx and the subsequent year t=tx+1 is denoted as AChange i j=n t=tx. The area that is expected to change corresponds to the difference in areas that the land-use type covers before and after the change.

AChange i j=n t=tx = Ai j=n t=tx+1 – Ai j=n t=tx (B.2)

8 In the estimation of carbon-stock changes from land uses that change, the equations distinguish between land uses. This distinction may or may not coincide with the distinction between species. Later, when estimating carbon-stock changes from land uses that remain, the equations distinguish between species. For reasons of consistency with equations in the subsequent part of the methodology, the notation names species as well as land-use types. See also footnote 15.


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where:

AChange ijt Area of the species (= land-use type) j that is expected to change, in stratum i, between the year t=tx and t=tx+1; ha

tx Starting year of a land-use change

Aijt Area of stratum i, species (= land-use type) j, at time tx; ha

(3) Determine the sum of carbon-stock changes for the area expected to remain from Step 2a for each land-use type (∆CRemain in Equation (B.3) and ∆CLB + ∆CDW + ∆CLI in Equation (B.7).

(a) For those land-use types without growing trees or woody perennials, the sum of carbon stock changes in above- and below-ground biomass, deadwood and litter is set as zero;

(b) For those land-use types with growing trees or woody perennials, the sum of carbon stock changes in above- and below-ground biomass of living trees, deadwood and litter is determined based on Equations (B.8) and (B.31).

(c) For shifting cultivation and fallow agriculture systems with various phases, the sum of carbon-stock changes is set as zero.

(4) Determine the sum of carbon-stock changes from areas that change from Step 2b (∆CChange in Equation (B.3). The carbon-stock changes from land-use change correspond to the sum of the carbon-stock changes from decreases and increases thanks to area-changes of the individual land uses.

(5) Sum the baseline net GHG removals by sinks across all strata.

The baseline is determined ex ante and remains fixed on per ha basis during the subsequent crediting period. Thus the baseline is not monitored.

This baseline methodology accounts for all carbon pools, except soil organic carbon. Therefore, the baseline net greenhouse gas removals by sinks can be calculated by the following equation:9

CBSL = ∆CRemain + ∆CChange (B.3)

where:

CBSL Baseline net greenhouse gas removals by sinks; t CO2-e

∆CRemain Sum of the changes in the stocks of all biomass pools from land uses that remain; t CO2-e

∆CChange Sum of the changes in the stocks of all biomass pools from land uses that change; t CO2-e

Note: In this methodology Equation (B.3) is used to estimate baseline net greenhouse gas removal by sinks for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which baseline net greenhouse gas removals by sinks are estimated.

9 In this determination, biomass-stock changes in land uses without growing trees or woody perennials are ignored, as

long as the land use does not change. Carbon-stock changes when land use changes are calculated in a conservative manner for both land-use with and without growing trees or woody perennials.


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5.3. Estimation of baseline carbon stock changes from land uses that change

The sum of the changes in all biomass stocks from land uses that change shall be estimated by:

∆CChange = ∑∑∑= = =

*

1 1 1

t

t

m

i

s

j

BL BL

(Cdecrease ijt + Cincrease ijt) · MWCO2-C (B.4)

where:

∆CChange Sum of the carbon-stock changes in all biomass pools from land uses that change; t CO2-e

Cincrease ijt Increases Annual increase in carbon stock in all biomass pools due to increasing areas for stratum i, species (= land-use type) j, calculated at time t; t C

Cdecrease ijt Decreases Annual decrease in carbon stock in all biomass pools due to decreasing areas for stratum i, species (= land-use type) j, at time t; t C

i 1, 2, 3, … mBL baseline strata

j 1, 2, 3, … sBL baseline species (= land-use types)

Note: j is termed “species” in most of this methodology; however, it really means “baseline vegetation” of “woody and non-woody species”. In concordance with this provision and for the purpose of Equation (B.4) we are looking at baseline land uses that are significantly different categories in terms of expected carbon stocks and carbon-stock changes in the carbon pools.

t 1, 2, 3, … t* years elapsed since the start of the A/R CDM project activity

MWCO2-C Ratio of molecular weights of CO2 and C (44/12); t CO2 (t C)-1

Note: Cincrease ijt is always greater or equal to 0. Cdecrease ijt is always less or equal to 0. In a given year and a given stratum, and for a specific land-use type, only one of the two can be different from 0, because one land-use type can only either increase or decrease but never both.

Note: The carbon stock change resulting from land-use change at a specific site is considered the sum of two components. For instance, 1 ha of sugar cane (8 t C per ha) is converted into 1 ha of pasture (5 t C per ha). The conversion entails a decrease of the carbon stock of sugar cane in the specific stratum and the specific year, and an increase of the carbon stock of pasture in the specific stratum and the specific year. The resulting carbon-stock change is the sum of a decrease of – 8 t C and an increase of + 5 t C, that is, the overall carbon-stock change corresponds to –3 t C.

In order to be conservative, the carbon stock of a land use shall be determined in a different yet parallel way for areas with increasing area (Cincrease ijt) and for land uses with decreasing area (Cdecrease ijt).

If AChange ijt > 0 (i.e., according to Equation (B.2), Ai j t=tx+1 > Ai j=n t=tx), then:

Cincrease ijt = AChange ijt · Bijt · CFj (B.5)

If AChange ijt < 0 (i.e., according to Equation (B.2), Ai j t=tx+1 < Ai j=n t=tx), then:

Cdecrease ijt = AChange ijt · Bijt · CFj (B.6)


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where:

Cincrease ijt Annual increase in carbon stock in all biomass pools due to increasing areas for stratum i, species (= land-use type) j, calculated at time t, i.e. between a given year tx and the subsequent year tx+1; t C

Cdecrease ijt Annual decrease in carbon stock in all biomass pools due to decreasing areas for stratum i, species (= land-use type) j, at time t, i.e. between a given year tx and the subsequent year tx+1; t C

AChange ijt Annual area of a species (= land-use type) j expected to change between a given year tx and the subsequent year tx+1 in stratum i; ha

Note: AChange ijt is less than 0 if the area decreases and greater than 0 if the area increases. If AChange ijt equals 0, the area remains, and the equations further below in this section must be applied.

Bijt Average biomass stock on land before or after the land-use change for stratum i, species (= land-use type) j, time t; t d.m. ha-1

Note: This value will be different if the land use’s area decreases or increases.

CFj Carbon fraction of dry biomass in woody tree or non-tree vegetation of species j, as appropriate; t C (t d.m.)-1

The biomass stocks of areas that change (Bijt) shall be determined by the below provisions (a-c). If carbon stocks are expected to increase due to land-use change to a land use type without trees or woody perennials, this methodology assumes conservatively that the carbon-stock changes occur instantly upon land-use change, whereas in reality they only occur over various years when carbon stocks approach a new equilibrium after the land-use change.

This does, however, not apply when an area changes to a land use with trees or woody perennials, in which case it is assumed that in the year of land-use change the carbon stocks change to those of a recently transformed area (for example a newly reforested area). Then, in the following years the carbon stocks increase over time according to the growth-based equations given further below in this methodology.

(a) For each of the land-use types without trees or woody perennials, determine biomass stocks at maturity. The biomass stocks can be determined either based on local or national or IPCC default parameters, or based on local inventories;

• If the area of the land-use type is expected to increase then assume for those areas that are added an instant growth to the biomass stock at maturity. This is a conservative provision, because the time it would take to reach stocks at maturity is not taken into consideration;

• If the area of the land-use type is expected to decrease then assume for those areas that are subtracted that their biomass is removed fully upon conversion. This is a conservative provision, because the biomass on the land use after conversion is assumed to grow to maturity upon conversion as well. This is based on the assumption that any residual carbon stocks in the litter pool from the previous land use, that could realistically remain after land conversion, will be smaller than the carbon stocks at maturity of the new land use, which is a safe assumption to make.


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(b) For each of the land uses with growing trees or woody perennials:

• If the area of the land-use type is expected to increase then assume for those areas that are added the biomass stock for a recently transformed area. This is a realistic provision. In following years these areas will then be treated as areas without land-use change, and the growth-based equations below are applied;

• If the area of the land-use type is expected to decrease then assume for those areas that are subtracted that they contained the biomass stock of the youngest areas covered by the land-use types in the given baseline year, if applicable. This is a conservative provision, because it likely underestimates the carbon-stock decrease.

Note: If the land-use type corresponds to “forest”, then the area of the land-use type is not expected to decrease, since the land-use change tabular representation excludes any land-use change events corresponding to deforestation. This methodology excludes the possibility of deforestation in the baseline. Therefore, this rule only applies to non-forest land with woody perennials of which the age is known.

(c) For shifting cultivation/fallow agriculture systems, the carbon stocks can be determined either based on local or national or IPCC default parameters, based on local inventories, and (as appropriate) based on regional surveys about management practices.

• If the area of the land-use type is expected to increase use the average stock over the fallow cycle. This is a reasonable provision, because it adequately represents an average carbon stock;

• If the area of the land-use type is expected to decrease use the average stock over the fallow cycle. This is a reasonable provision, because it adequately represents an average carbon stock.

5.4. Estimation of baseline carbon-stock changes from land uses that remain10

The sum of the changes in all biomass stocks from land uses that remain shall be estimated in the individual biomass pools by the following provisions:11

∆CRemain = ∆CLB + ∆CDW + ∆CLI (B.7)

where:

∆CRemain Sum of the changes in the stocks of the biomass pools from land uses that remain; t CO2-e

∆CLB Sum of the changes in biomass carbon stocks of living trees (above- and below-ground) of land uses that remain; t CO2-e

∆CDW Sum of the changes in deadwood carbon stocks of land uses that remain; t CO2-e

∆CLI Sum of the changes in litter carbon stocks of land uses that remain; t CO2-e

10 The remainder of this section deals with areas that continue to be covered by the same land-use type (=species)

between years. Consistently with the above notation, this is ARemain, where AChange denotes changing areas, and A represents the total area, including both changing and remaining areas. Other methodologies only deal with areas that continue to be covered by the same land-use type (=species). What other methodologies denote Aijt, this methodology denotes ARemain ijt.

11 Following GPG-LULUCF Equation 3.2.1


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5.4.1. Estimation of baseline ∆CLB (changes in biomass carbon stocks of living trees)

∆CLB = ∑∑∑= = =

*

1 1 1

t

t

m

i

s

j

BL BL

∆CLB ijt*1 year (B.8)

where:

∆CLB Sum of the changes in biomass carbon stocks of living trees (above- and below-ground); t CO2-e

∆CLB ijt Annual carbon stock change in living biomass of trees for stratum i, species j, time t; t CO2-e yr-1


j 1, 2, 3, … sBL baseline tree species12

t 1, 2, 3, …t* years elapsed since the start of the A/R CDM project activity

For those strata without growing trees or woody perennials, ∆CLB ijt = 0. For those strata with a few growing trees, ∆CLB ijt is estimated using one of following two methods that can be chosen based on the availability of data.

Method 1: carbon gain-loss method13

∆CLB ijt = ∆CG, ijt - ∆CL, ijt (B.9)

where:


∆CG, ijt Annual increase in carbon stock due to biomass growth of trees for stratum i, species j, time t; t CO2-e yr-1

∆CL, ijt Annual decrease in carbon stock due to biomass loss of trees for stratum i, species j, time t; t CO2-e yr-1

∆CG, ijt = ARemain ijt · GTOTAL, ijt · CFj · MWCO2-C (B.10)

12 The baseline vegetation in stratum i may include one or more woody and non-woody species. Project proponents

shall identify the individual species, group of species or vegetation cohorts – in the equations of this methodology referred to with the letter j (“tree species”) - that represent homogeneous and significantly different categories in terms of expected carbon stock changes in the carbon pools. See also footnote 11.

13 GPG-LULUCF Equation 3.2.2, Equation 3.2.4 and Equation 3.2.5.


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where:

∆CG, ijt Annual increase in carbon stock due to biomass growth of trees for stratum i, species j, time t; t CO2-e yr-1

ARemain ijt Area of the species j that is expected to remain, in stratum i, between year t and t+1; ha

GTOTAL,ijt Annual average increment rate in total biomass of trees in units of dry matter for stratum i, species j, at time t; t d.m ha-1 yr-1

Note: GTOTALijt can be estimated as a constant annual average value.

CFj The carbon fraction for species j; t C (t d.m)-1


GTOTAL,ijt = Gw,ijt · (1+Rj) (B.11)

Gw,ijt = Iv, ijt · Dj · BEF1, j (B.12)

where:

GTOTAL,ijt Annual average increment rate in total biomass of living trees in units of dry matter for stratum i, species j, at time t; t d.m ha-1 yr-1

Gw,ijt Average annual aboveground dry biomass increment of living trees for stratum i, species j, at time t; t d.m ha-1 yr-1

Rj Root-shoot ratio appropriate to increments for tree species j; dimensionless

Note: Care should be taken that the root-shoot ratio may change as a function of the above-ground biomass present at time (t) (see IPCC GPG, 2003, Annex 3.A1, Table 3A1.8)

Iv,ijt Average Annual increment in merchantable volume for stratum i, species j; m3 ha-1 yr-1

Note: Ivijt is estimated as “current annual increment – CAI”. The “mean annual incremente” – MAI in the forestry jargon – can only be used if its use leads to conservative estimates.

Dj Basic wood density for species j; t d.m. m-3

BEF1,j Biomass expansion factor for conversion of annual net increment (including bark) in merchantable volume to total aboveground biomass increment for tree species j, dimensionless

If the annual increment in merchantable volume for stratum i, species j (Iv,ijt) applied in the Equation (B.12) is the gross increment then the following equations shall be used to calculate the average annual decrease in carbon stocks due to biomass loss of living trees.14 15

∆CL, ijt = Lhr, ijt + Lfw, ijt + Lot, ijt (B.13)

14 It is more likely that these equations will be used for estimating the project-scenario verifiable changes in the

stocks of the carbon pools than for estimating the baseline net GHG removals. Nevertheless, this methodology includes them here already for reasons of consistency.

15 Refers to GPG-LULUCF Equation 3.2.6, Equation 3.2.7, Equation 3.2.8 and Equation 3.2.9.


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where:

∆CL, ijt Average annual decrease in carbon stocks due to biomass loss of living trees for stratum i, species j, time t; t CO2-e yr-1

Lhr, ijt Annual carbon loss of living trees due to commercial harvesting for stratum i, species j, time t; t CO2-e yr-1

Lfw, ijt Annual carbon loss of living trees due to fuel wood gathering for stratum i, species j, time t; t CO2-e yr-1

Lot, ijt Annual natural carbon losses (mortality) of of living trees for stratum i, species j, time t; t CO2-e yr-1

Lhr, ijt = Hijt · Dj · BEF2, j · CFj · ARemain ijt · MWCO2-C (B.14)

Lfw, ijt= FGijt · Dj · BEF2, j · CFj · ARemain ijt · MWCO2-C (B.15)

Lot, ijt= Bw,ijt · Mijt · CFj · Adistijt · MWCO2-C (B.16)

where:

Lhr, ijt Annual carbon loss due to commercial harvesting for stratum i, species j, time t; t CO2-e yr-1

Lfw, ijt Annual carbon loss due to fuel wood gathering for stratum i, species j, time t; t CO2-e yr-1

Lot, ijt Annual natural losses (mortality) of carbon for stratum i, species j, time t; t CO2-e yr-1

Hijt Annually extracted merchantable volume for stratum i, species j, time t; m3 ha-1 yr-1

Note: The time notation t is given here assuming that in most cases project participants are able to define a harvesting schedule (volumes and years of harvesting). A constant average annual harvesting volume should be used only under particular circumstances and should be justified in the PDD.

Dj Basic wood density for species j; t d.m. m-3 merchantable volume

BEF2,j Biomass expansion factor for converting merchantable volumes of extracted roundwood to total aboveground biomass (including bark) for tree species j, dimensionless

CFj Carbon fraction of woody dry matter for species j; t C (t d.m.)-1



Mijt Mortality factor = fraction of above-ground biomass stock of living trees for stratum i, species j that died during year t;dimensionless


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FGijt Annual volume of fuel wood harvesting of living trees for stratum i, species j, time t; m3 yr-1

Note: See note made for Hijt.

Adistijt Forest areas affected by disturbances in stratum i, species j, time t; ha yr-1

Bw, ijt Average above-ground biomass stock of living trees for stratum i, species j, time t; t d.m. ha-1

The choices of methods and parameters shall be made in the same ways as described in Section II.5.

This methodology allows assuming no disturbances in the ex ante16 estimation of actual net GHG removals by sinks, which implies that Adistijt is set as zero and therefore Lot,ijt = 0. This assumption can be made in project circumstances where expected disturbances (e.g. fire, pest and disease outbreaks) are of low frequency and intensity. However, the factor Adistijt should be estimated when natural tree mortality due to competition and/or disturbances is likely to result in significant carbon losses. In such cases, Adistijt can be estimated as an average annual percentage of Aijt to express a yearly mortality percentage due to competition (usually between 0% and 2% of Aijt) and/or disturbances.

Method 2: stock change method17

∆CLB ijt = (C LB ijt 2 - C LB ijt 1)/T · MWCO2-C (B.17)

C LB ijt = CAB, ijt + CBB, ijt (B.18)

CAB, ijt = ARemain ijt · Vijt · Dj · BEF2, j · CFj (B.19)

CBB, ijt = CAB, ijt · Rj (B.20)

where:

∆CLB ijt Total carbon-stock change in living biomass of trees for stratum i, species j, at time t; t CO2 -e year-1 yr-1

CLB ijt Total carbon stock in living biomass of trees for stratum i, species j, at time t; t C

CLB ijt2 Total carbon stock in living biomass of trees for stratum i, species j, calculated at time t=t2; t C

CLB ijt1 Total carbon stock in living biomass of trees for stratum i, species j, calculated at time t=t1; t C

T Number of years between times t2 and t1 (T = t2-t1); yearsyr


16 The baseline methodology assumes that a monitoring methodology will be used for ex post mandatory accounting

of disturbances. 17 GPG-LULUCF Equation 3.2.3.


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CAB,ijt Carbon stock in above-ground biomass of living trees for stratum i, species j, at time t; t C

CBB,ijt Carbon stock in below-ground biomass of living trees for stratum i, species j, at time t; t C

Vijt Average merchantable volume of stratum i, species j, at time t; m3 ha-1

Dj Basic wood density for species j; t d.m. m-3 merchantable volume

BEF2,j Biomass expansion factor for conversion of merchantable volume to aboveground tree biomass for species j; dimensionless

CFj The carbon fraction for species j; t C (t d.m)-1

Rj Root-shoot ratio species j; dimensionless

The time points 1 and 2, for which the stock are estimated taken to determine the ∆CLB ijt must be broadly representative of the typical age of the trees under the baseline scenario during the crediting period.

The combinations of strata and species shall be developed and presented in the PDD in a way that the values of Vijt (average merchantable volume of stratum i, species j, at time t) used in Equation (B.21) represent the actual average merchantable volume of stratum i, species j, at time t after deduction of harvested volumes and mortality:18

Vijt2 = Vijt1 · (1 – MfijT)+ (Iv, ijT – HijT – FGijT) · T (B.21)

MfijT = AdistijT / AijT (B.22)

where:

Vijt2 Average merchantable volume of stratum i, species j, at time t = t2; m3 ha-1

Vijt1 Average merchantable volume of stratum i, species j, at time t = t1; m3 ha-1

MfijT Mortality factor = fraction of Vijt1 died during the period T; dimensionless

Iv,ijT Average annual net increment in merchantable volume for stratum i, species j during the period T; m3 ha-1 yr-1

HijT Average annually harvested merchantable volume for stratum i, species j during the period T; m3 ha-1 yr-1

FGijT Average annual volume of fuel wood harvested for stratum i, species j, during the period T; m3 ha-1 yr-1

T Number of years between times t2 and t1 (T = t2 - t1); years

AdistijT Average annual area affected by disturbances for stratum i, species j, during the period T; ha yr-1

AijT Average annual area for stratum i, species j, during the period T; ha yr-1

18 It is more likely that these equations will be used for estimating the project-scenario verifiable changes in the

stocks of the carbon pools than for estimating the baseline net GHG removals. Nevertheless, this methodology includes them here already for reasons of consistency.


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An alternative way of estimating CAB,ijt is to use allometric equations which are also considered to be good practice by the IPCC.and other recognized experts in the field of forestry.

CAB, ijt = ARemain ijt · nTrijt · CFj · fj(DBHt, Ht) (B.23)

where:

CAB,ijt Carbon stock in above-ground biomass of living trees for stratum i, species j, at time t; t C


nTRijt Number of trees in stratum i, species j, at time t; ha-1

CFj Carbon fraction of woody dry matter for species j; t C (t d.m)-1

fj(DBHt,Ht) Allometric equation linking above-ground biomass of living trees (t d.m.ha-1) to mean diameter at breast height (DBHt) and possibly meantree height (Ht) for species j; t d.m. ha-1

Note: Mean DBH and H values should be estimated for stratum i, species j, at time t using a growth model or yield table that gives the expected tree dimensions as a function of tree age. The allometric relationship between above-ground biomass of trees and DBH and possibly H is a function of the species considered. However, when several species or groups of species are present in a vegetation category or in a planted stand, allometric equations can also be developed for a group of species or for the dominant species to represent a particular species mix or vegetation cohort.

For the choice of methods 1 or 2 above, there is no priority in terms of transparency and conservativeness. The choice should mainly depend on the kind of parameters available. Vijt and Iv,ij shall be estimated based on number of trees and national/local growth curve/table that usually can be obtained from national/local forestry inventory. Dj, BEF1,j, BEF2,j, CFj and Rj are regional and species specific and shall be chosen with priority from higher to lower order as follows:

1. Locally-derived species-specific information, if sufficiently accurate and comprehensive data are available;

2. Species-specific information from regional datasets, or species-specific information extracted from national datasets for sites with similar soil and climatic conditions;

3. Species-specific information extracted from nationally-derived datasets avoiding only sites with very different soil and climate conditions;

4. Locally-, regionally-, or nationally-derived information for similar species;

5. Default values provided by the IPCC (e.g. IPCC 2003, Annex 3A.1, Annex 4A.2) or other scientific sources.

When choosing from global or national databases because local data are limited, it shall be confirmed with any available local data that the chosen values for the baseline are do not lead to a significant underestimate of the baseline net removals by sinks, as far as can be judged. Local data used for confirmation may be drawn from the literature and local forestry inventory, or measured directly by project participants especially for BEF and root-shoot ratios that are age- and species- dependent.


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5.4.2. Estimation of baseline ∆CDW (changes in deadwood carbon stocks)

Baseline deadwood carbon stocks increase due to the mortality of living biomass of trees and the accumulation of residues from harvesting operations remaining on the ground, and decreases due to partial harvesting (e.g. fuel wood collection) and wood decomposition:

∑∑∑= = =

∆=∆*

1 1 1

t

t

m

i

s

jijtDWDW

BL BL

CC

yearCCt

t

m

i

s

jijtDWDW

BL BL

1**

1 1 1∑∑∑

= = =

∆=∆ (B.24)

where:

∆∆CDW Sum of the changes in deadwood carbon stocks; t CO2-e (as per Equation (B.7))

∆CDW ijt Annual carbon stock change in deadwood for stratum i, species j, time t; t CO2-e yr-1


j 1, 2, 3, … sBL baseline tree species


Method : carbon gain-loss method

∆CDW ijt = ∆CmlbDW ijt + ∆ChrDW ijt - ∆CfwDW ijt - ∆CdescDW ijt (B.25)

where:

∆CDW ijt Annual carbon stock change in the deadwood carbon pool for stratum i, species j, time t; t CO2-e yr-1

∆CmlbDW ijt Annual increase of carbon stock in the deadwood carbon pool due to mortality of the living biomass of trees for stratum i, species j, time t; t CO2-e yr-1

∆ChrDW ijt Annual increase of carbon stock in the deadwood carbon pool due to harvesting residues not collected for stratum i, species j, time t; t CO2-e yr-1

∆CfwDW ijt Annual decrease of carbon stock in the deadwood carbon pool due to harvesting of deadwood for stratum i, species j, time t; t CO2-e yr-1

∆CdescDW ijt Annual decrease of carbon stock in the deadwood carbon pool due to deadwood decomposition for stratum i, species j, time t; t CO2-e yr-1

The following equations shall be used:

∆CmlbDW ijt = jjjijtijt CFBEFDwMfV ⋅⋅⋅⋅ ,2 · ARemain ijt · MWCO2-C (B.26)

∆ChrDW ijt = jjjijtijt CFBEFDwHfH ⋅⋅⋅⋅ ,2 · ARemain ijt · MWCO2-C (B.27)


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∆CfwDW ijt = 1, −⋅ tijDWijt CFwf (B.28)

∆CdescDW ijt = 1, −⋅ tijDWCDC (B.29)

and CDWij,t=1=∆CmlbDW ijt=1 (needed to intiate calculation of ∆CfwDW ijt and ∆CdescDW ijt ).

where:

∆CmlbDW ijt Annual increase of carbon stock in the deadwood carbon pool due to mortality of the living biomass of trees for stratum i, species j, time t; t CO2-e yr-1

Vijt Average merchantable volume of stratum i, species j, at time t; m3 ha-1

Mfijt Mortality Annual mortality factor = fraction of Vijt dying annually at time t; yr-1

dimensionless

Dwj Intermediate19 deadwood density for species j; t d.m. m-3 merchantable volume

BEF2,j Biomass expansion factor for converting merchantable volumes of extracted round wood to total above-ground biomass (including bark) for stratum i, species j, time t; dimensionless

CFj Carbon fraction of woody dry matter for species j; t C (t d.m)-1


Hijt Average Annually harvested merchantable volume for stratum i, species j, time t; m3 ha-1 yr-1

∆ChrDW ijt Annual increase of carbon stock in the deadwood carbon pool due in to harvesting residues remaining on site not collected for stratum i, species j, time t; t CO2-e yr-1

Hfijt Fraction of annually harvested merchantable volume not extracted and left on the ground as harvesting residue for stratum i, species j, time t; dimensionless

∆CfwDW ijt Annual decrease of carbon stock in the deadwood carbon pool due to harvesting of deadwood for stratum i, species j, time t; t CO2-e yr-1

Fwfijt Fraction of annually harvested deadwood carbon stock harvested annually as fuel wood for stratum i, species j, time t; yr-1 dimensionless

CDWij,t-1 Carbon stock in the deadwood carbon pool in stratum i, species j, time t = t-1 year; t CO2-e

∆CdescDW ijt Annual decrease of carbon stock in the deadwood carbon pool due to deadwood decomposition for stratum i, species j, time t; t CO2-e yr-1

DC Decomposition rate (% (fraction of carbon stock in total deadwood stock decomposed annually); yr-1dimensionless


19 Each deadwood piece should be assigned to one of three density states – sound, intermediate, and rotten –(Warren,

W.G. and Olsen, P.F. 1964. A line transects technique for assessing logging waste. Forest Science 10: 267-276). In absence of ex ante data, intermediate densities should be assumed.


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Project proponents shall make conservative estimates of the parameters used in Equations (B.26) to (B.29) using the best information available to them. If these equations are used for monitoring, the parameters shall be updated, once data from monitoring will become available. The values used for the variables (e.g. Vijt and Mfijt and Hijt) shall be consistent with the values used in Equation (B.21).

Method:stock change method

∆CDW ijt = (CDW ijt 2 – CDW ijt 1)/T · MWCO2-C (B.30)

where:

∆CDW ijt Annual carbon stock change in the deadwood carbon pool for stratum i, species j, time t; t CO2-e yr-1

CDW ijt2 Total carbon stock in deadwood for stratum i, species j, calculated at time t=t2; t C

C DW ijt1 Total carbon stock in deadwood for stratum i, species j, calculated at time t=t1; t C

T Number of years between times t2 and t1 (T = t2-t1); years yr


5.4.3. Estimation of baseline ∆CLI (changes in litter carbon stocks)

Baseline litter carbon stocks increase due to the mortality of living biomass and the accumulation of residues from harvesting operations remaining on the ground, and decreases due to partial harvesting (e.g. fuel wood collection) and wood decomposition:

∆CLI = ∑∑∑= = =

∆*

1 1 1

t

t

m

i

s

jijtLI

BL BL

C *1 year (B.31)

where:

∆CLI Sum of the changes in litter carbon stocks; t CO2-e (as per Equation (B.7))

∆CLI ijt Annual carbon stock change in litter for stratum i, species j, time t; t CO2-e yr-1

i 1, 2, 3, … mBL strata in the baseline

j 1, 2, 3, … sPS tree species in the project scenario

t 1, 2, 3, …t* years elapsed since the start of the A/R CDM project activity

Method 1: carbon gain-loss method

∆CLI ijt = ∆CmlbLI ijt + ∆ChrLI ijt - ∆CfwLI ijt - ∆CdescLI ijt (B.32)


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where:

∆CLI ijt Annual carbon stock change in the litter carbon pool for stratum i, species j, time t; t CO2-e yr-1

∆CmlbLI ijt Annual increase of carbon stock in the litter carbon pool due to mortality of the living biomass of trees for stratum i, species j, time t; t CO2-e yr-1

∆ChrLI ijt Annual increase of carbon stock in the litter carbon pool due to harvesting residues not collected for stratum i, species j, time t; t CO2-e yr-1

∆CfwLI ijt Annual decrease of carbon stock in the litter carbon pool due to harvesting of litter for stratum i, species j, time t; t CO2-e yr-1

∆CdescLI ijt Annual decrease of carbon stock in the litter carbon pool due to litter decomposition for stratum i, species j, time t; t CO2-e yr-1

Method 2 (stock change method)

∆CLI ijt = (CLI ijt 2 – CLI ijt 1)/T · MWCO2-C (B.33)

∆CLI ijt Annual carbon stock change in the litter carbon pool for stratum i, species j, time t; t CO2-e yr-1

CLI ijt2 Total carbon stock in litter for stratum i, species j, calculated at time t=t2; t C

CLI ijt1 Total carbon stock in litter for stratum i, species j, calculated at time t=t1, t C

T Number of years between times t2 and t1 (T = t2-t1)


6. Ex ante actual net GHG removals by sinks

In choosing parameters and making assumptions project participants should retain a conservative approach, i.e. if different values for a parameter are plausible, a value that does not lead to an overestimation of the actual net GHG removals by sinks or underestimation of the baseline bet GHG removals by sinks should be applied.

The actual net greenhouse gas removals by sinks represent the sum of the verifiable changes in carbon stocks in the carbon pools within the project boundary, minus the increase in non-CO2 GHG emissions measured in CO2 equivalents by sources that are increased as a result of the implementation of an A/R CDM project activity, while avoiding double counting, within the project boundary, attributable to the A/R CDM project activity. Therefore,

CACTUAL = ∆CLB + ∆CDW + ∆CLI – EBiomassloss – GHGE (B.34)


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where:

CACTUAL Actual net greenhouse gas removals by sinks; t CO2-e

∆CLB Sum of the changes in living biomass carbon stocks of trees (above- and below-ground); t CO2-e

∆CDW Sum of the changes in deadwood carbon stocks; t CO2-e

∆CLI Sum of the changes in litter carbon stocks; t CO2-e

GHGE Sum of the increases in GHG emissions by sources within the project boundary as a result of the implementation of an A/R CDM project activity; t CO2-e

Ebiomassloss Decrease in the carbon stock in the tree and non-tree living biomass, deadwood and litter carbon pools of pre-existing vegetation in the year of site preparation up to time t*; t CO2-e

Note: In this methodology Equation (B.34) is used to estimate actual net greenhouse gas removal by sinks for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated.

Note: In Equation (B.34) ∆CLB does not distinguish between pre-existing vegetation and trees planted under the project activity, but ∆CLB includes both. This is possible, because the project initially takes a discount for the biomass stored in pre-existing vegetation with EBiomassloss. The 100% decrease in the carbon stocks of the pre-existing vegetation is an initial loss, and therefore accounted for only once upfront as part of the first monitoring interval, not per year. Later, remainders of pre-existing vegetation are accounted for along with the project vegetation.

6.1. Verifiable changes in the carbon stocks in the carbon pools

6.1.1. Treatment of pre-existing vegetation

The methodology considers the two following possible situations:

(a) The carbon stocks in the tree and non-tree living biomass, deadwood and litter of pre-existing vegetation are not significant (i.e., they are not likely to represent more than 2% of the anticipated actual net GHG removals by sinks):

• Carbon stock changes in the tree and non-tree living biomass of pre-existing vegetation, deadwood and litter are not included in the ex ante calculation of actual carbon stock changes, regardless if the pre-existing vegetation is left standing, burnt for land preparation, or is harvested;

• If the pre-existing vegetation is burned for land preparation before planting, non-CO2 emissions are estimated from the tree and non-tree above-ground biomass, deadwood and litter (details in Section 2 below) and included in the calculation of actual net GHG removal by sinks if they are significant (> 2% of actual net GHG removals by sinks);

• To be realistic, the biomass of the pre-existing vegetation would be set as the average biomass over a slash and burn/fallow cycle;

(b) The carbon stocks in the tree and non-tree living biomass, deadwood and litter of pre-existing vegetation are significant.


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If the carbon stocks in the pre-existing vegetation are significant, i.e., they are likely to represent more than 2% of the anticipated actual net GHG removals by sinks, the following methodology procedure is applied:

• If the baseline is shifting agriculture or another form of agriculture/fallow cycle, it is a realistic approach to set the baseline stock to be equal to the average stock over the cycle. It is assumed all this stock will be removed in the year of site preparation. The stocks are assumed to be burned:

o Non-CO2 emissions are calculated from the carbon stock in the tree and non-tree above-ground biomass, deadwood and litter (details in Section II.6.2) below);

o 100% carbon stock loss in the above- and below-ground biomass, deadwood and litter is assumed and estimated using Equation (B.35) for both the non-tree component and the young trees.

• Otherwise if for land preparation before planting non-tree and tree vegetation is burned (and not harvested) then:

o Non-CO2 emissions are calculated from the carbon stock in the tree and non-tree above-ground biomass, deadwood and litter (details in Section II.7.2) below);

o 100% carbon stock loss in the above-and below-ground biomass, deadwood and litter is assumed and estimated using the methods outlined in Equation (B.36) below for the tree component and deadwood and litter and Equation (B.35) for the non-tree component.

• Or, if the tree vegetation is partially or totally harvested before burning then:

o The carbon stock decrease in the harvested above- and below-ground tree biomass is estimated using the methods outlined below;

o The above-ground biomass of the harvested trees is subtracted from the biomass estimate (including tree and non-tree above-ground biomass, deadwood and litter) used for the calculation of non-CO2 emissions from burning;

o Carbon stock changes in the tree and non-tree living biomass, deadwood and litter of pre-existing vegetation (e.g., trees that are left standing) are not included in the ex ante and ex post calculation of actual carbon stock changes. This is a conservative assumption because the trees will continue to grow.

All pre-existing tree and non-tree vegetation as well as all deadwood and litter can be assumed to be removed in the year of site preparation, to account for slash and burn or future competition from planted trees. This is a conservative assumption because there will be some non-tree vegetation in the project scenario. Some vegetation may re-grow even if all non-tree vegetation is removed during the site preparation (overall site burning). Moreover, this is a conservative assumption, because some trees may not be removed during site preparation, or slash and burn may not occur at all.

The carbon stock decrease is estimated as follows:

Ebiomassloss = ∑∑∑= = =

*

1 1 1

t

t

m

i

S

j

BL PS

Aijt * Bpre ijt * CFpre * MWCO2-C (B.1)

Ebiomassloss = ∑∑= =

BL PSm

i

S

j1 1Aijt * Bpre ijt * CFpre * MWCO2-C (B.35)


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where:


Aijt Area of stratum i, species j, time t; ha

Bpre,ijt Average pre-existing stock of pre-project biomass in the tree and non-tree living biomass, deadwood and litter carbon pools on land to be planted before the start of a proposed A/R CDM project activity for baseline stratum i, species j, time t; t d.m. ha-1

CFpre The carbon fraction of dry biomass in pre-existing vegetation, t C (t d.m.)-1

MWCO2-C Ratio of molecular weights of CO2 and carbon; t CO2-e (t C)-1

i 1, 2, 3, … mBL strata in the baseline


t 1, 2, 3, … t* year of site preparation on area of stratum i, species j years elapsed since the start of the A/R CDM project activity

The methodology and equations for estimating ex ante actual changes in the living biomass carbon stocks of trees are similar to the ones used for the estimation of baseline changes in the living biomass carbon stocks of trees:

∑∑∑= = =

∆=∆*

1 1 1

t

t

m

i

s

jLBijtLB

PS PS

CC *1 year (B.36)

where:



i 1, 2, 3, … mPS strata in the project scenario



The average annual carbon stock change in above- and belowground biomass in living trees between two monitoring events at time t, for stratum i, species j (∆CLB ijt) shall be estimated using one of the two methods described in Section II.5.4.1, i.e., Equations (B.8) to (B.23).

6.1.2. Estimation of actual ∆CDW (changes in deadwood carbon stocks)

As in the case of the living biomass, carbon stock changes in the deadwood carbon pools can be estimated using a carbon gain-loss method or a stock change method.

∑∑∑= = =

∆=∆*

1 1 1

t

t

m

i

s

jijtDWDW

PS PS

CC *1 year (B.37)


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where:

∆CDW Sum of the changes in deadwood carbon stocks; t CO2-e (as per Equation (B.34))

∆CDW ijt Annual carbon stock change in deadwood for stratum i, species j, time t; t CO2-e yr-1




The average annual carbon stock change in deadwood at time t, for stratum i, species j (∆CDW ijt) shall be estimated using one of the two methods described in Section II.5.4.2. i.e., Equations B.24 to B.30.

6.1.3. Estimation of actual ∆CLI (changes in litter carbon stocks)

As in the case of the living biomass, carbon stock changes in the litter carbon pools can be estimated using a carbon gain-loss method or a stock change method.

∑∑∑= = =

∆=∆*

1 1 1

t

t

m

i

s

jijtLILI

PS PS

CC *1 year (B.38)

where:

∆CLI Sum of the changes in litter carbon stocks; t CO2-e (as per Equation (B.34)

∆CLI ijt Annual carbon stock change in litter for stratum i, species j, time t; t CO2-e yr-1




The average annual carbon stock change in litter between two monitoring events at time t, for stratum i, species j (∆CLI ijt) shall be estimated using one of the two methods described in Section II.5.4.3, i.e., Equations (B.31) to (B.33).

6.2. GHG emissions by sources

An A/R CDM project activity may increase GHG emissions, in particular CO2, CH4 and N2O. The list below contains factors that may be attributable to the increase of GHG emissions:20

• Emissions of greenhouse gases from combustion of fossil fuels for site preparation, thinning and logging;

• Emissions of non-CO2 greenhouse gases from biomass burning for site preparation (slash and burn activity);

• N2O emissions caused by nitrogen fertilization application.

The increase in GHG emission as a result of the implementation of the proposed A/R CDM project activity within the project boundary can be estimated by:

GHGE = EFuelBurn + ENon-CO2, BiomassBurn + N2Odirect-Nfertilizer (B.39)

20 Refer to Box 4.3.1 and Box 4.3.4 in IPCC GPG-LULUCF.


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where:

GHGE Increase in GHG emissions as a result of the implementation of the A/R CDM project activity within the project boundary, t CO2-e yr-1

EFuelBurn Total GHG emissions due to fossil fuel combustion from vehicles; t CO2-e yr

ENon-CO2, BiomassBurn Non-CO2 emission as a result of biomass burning within the project boundary; t CO2-e yr-1

N2Odirect-Nfertilizer Increase in direct N2O emission as a result of direct nitrogen application within the project boundary; t CO2-e yr-1

Note: In this methodology, Equation (B.37) is used to estimate the increase in GHG emission for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated.

6.2.1. Estimation of EFuelBurn (GHG emissions from burning of fossil fuels)

7. GHG emissions from the burning of fossil fuels could result from the use of machinery during site preparation and logging. These emissions can shall be calculated using the A/R Methodological Tool for “Estimation of GHG emissions related to fossil fuel combustion in A/R CDM project activities” where:

∑=

=*

1,

t

yyFCFuelBurn ETE * 1 year (B.40)

E FuelBurn = E Vehicle,CO2

and:

∑∑∑=

⋅=*

1, )(

2

t

txyt

x yxyCOVehicle mptionFuelConsuEFE

xytxytxytxyt eknptionFuelConsum ⋅⋅= (B.2)

where:

EFuelBurn Total GHG emissions due to fossil fuel combustion from vehicles; t CO2-e yr

ETFC,y CO2 emissions from fossil fuel combustion during the year y; t CO2

EVehicle,CO2 Total CO2 emissions due to fossil fuel combustion from vehicles; t CO2-e yr-1

EFxy CO2 emission factor for vehicle type x with fuel type y; dimensionless

FuelConsumptionxyt Recorded consumption of fuel type y of vehicle type x at time t; liters

nxyt Number of vehicles

kxyt Kilometers traveled by each of vehicle type x with fuel type y at time t; km

exyt Fuel efficiency of vehicle type x with fuel type y at time t; liters km-1

x Vehicle type

y Fuel type


The country-specific emission factors shall be used. There are three possible sources of emission factors:


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• National emission factors: These emission factors may be developed by national programmes such as national GHGs inventory

• Regional emission factors

• IPCC default emission factors, provided that a careful review of the consistency of these factors with the country conditions has been made. IPCC default factors may be used when no other information is available.

Project participants shall make conservative and credible assumptions of yearly fuel consumption taking into account travel distances, vehicle/machine fuel efficiency, machine hours, and timing of planting and harvesting. Whenever possible, the assumptions shall be supported by verifiable evidence.

6.2.2. Calculation of non-CO2 emissions from biomass burning

If slash and burn occurs during site preparation before planting and/or replanting, this results in non-CO2 emissions (CO2 emission has been covered above as decreases in the stocks of the carbon pools). Based on GPG for LULUCF,21 this type of emission can be estimated as follows:

422 ,,, CHnBiomassBurONnBiomassBurnBiomassBurCONon EEE +=−

42 ,, CHnBiomassBurnBiomassBurCONon EE =− (B.41)

EBiomassBurn, N2O = EBiomassBurn, C · (N/C ratio) ·ERatN2O · MWN2O-N · GWPN2O

EBiomassBurn, CH4 = EBiomassBurn, C · ERatCH4 · MWCH4-C · GWPCH4 (B.42)

where:22

ENon-CO2, BiomassBurn The i Increase in nNon-CO2 emission as a result of biomass burning in slash and burn; t CO2-e yr-1

EBiomassBurn, N2O N2O emission from biomass burning in slash and burn; t CO2-e yr-1

EBiomassBurn, CH4 CH4 emission from biomass burning in slash and burn; t CO2-e yr-1

EBiomassBurn,C Loss of carbon stock in aboveground biomass due to slash and burn; t C yr-1

N/C ratio Nitrogen-carbon ratio, t N (t C)-1

MWN2O-N Ratio of molecular weights of N2O and N (44/28); t N2O (t N)-1

MWCH4-C Ratio of molecular weights of CH4 and C (16/12); t CH4 (t C)-1

ERatN2O IPCC default emission ratio for N2O (0.007); dimensionless

ERatCH4 IPCC default emission ratio for CH4 (0.012); dimensionless

GWPN2O Global Warming Potential for N2O (310 for the first commitment period); t CO2-e (t N2O)-1

GWPCH4 Global Warming Potential for CH4 (21 for the first commitment period); t CO2-e (t CH4)-1

21 Refers to Equation 3.2.20 in GPG -LULUCF. 22 Refers to Table 5.7 in 1996 Revised IPCC Guideline for LULUCF and Equation 3.2.19 in GPG LULUCF.


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EBiomassBurn,C = ∑=

⋅⋅⋅PSm

iiiburn CFCEBA

1, (B.45)

EBiomassBurn,C = ∑∑= =

⋅⋅⋅*

1 1,,

t

t

m

iitiburn

PS

CFCEBA (B.43)

where

EBiomassBurn,C Loss of carbon stock in aboveground biomass due to slash and burn; t C yr-1

Aburn,i,t Area of slash and burn for stratum i in year t; ha yr-1

Bi Average stock in aboveground living biomass before burning for stratum i; t d.m. ha-1

CE Combustion efficiency (IPCC default =0.5); dimensionless

CF Carbon fraction of dry biomass; t C (t d.m)-1

i Stratum (mPS = total number of strata)


The combustion efficiencies may be chosen from Table 3.A.14 of GPG-LULUCF. If no appropriate combustion efficiency can be used, the IPCC default of 0.5 should be used, see Section 3.2.1.4.2.2 in GPG LULUCF.. The nitrogen-carbon ratio (N/C ratio) is approximated to be about 0.01. This is a general default value that applies to leaf litter, but lower values would be appropriate for fuels with greater woody content, if data are available.

6.2.3 Calculation of nitrous oxide emissions from nitrogen fertilization

Emissions of nitrous oxide from nitrogen fertilization is given by:23

N2Odirect-Nfertilizer = (FSN + FON ) · EF1 · MWN2O-N · GWPN2O (B.44)

FSN t = NSN-Fert,t · (1-FracGASF) (B.48)

FON t = NON-Fert t · (1-FracGASM) (B.49)

FSN t = ∑=

*

1

t

t

NSN-Fert,t · (1-FracGASF) (B.45)

FON t = ∑=

*

1

t

t

NON-Fert t · (1-FracGASM) (B.46)

23 Refers to Equation 3.2.18 in IPCC GPG-LULUCF.


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where:

N2Odirect-Nfertilizer Direct N2O emission as a result of nitrogen application within the project boundary up to time t*; t CO2-e

FSNt t Amount of synthetic fertilizer nitrogen applied at time t adjusted for volatilization as NH3 and NOX up to time t*; t N

FONtt Annual amount of organic fertilizer nitrogen applied at time t adjusted for volatilization as NH3 and NOX up to time t*; t N

NSN-Fert t Amount of synthetic fertilizer nitrogen applied annually at time t; t N

NON-Fert t Amount of organic fertilizer nitrogen applied annually at time t; t N

EF1 Emission factor for emissions from N inputs; t N2O-N (t N input)-1

FracGASF Fraction that volatilizes as NH3 and NOX for synthetic fertilizers; t NH3-N and NOX-N (t N)-1

FracGASM Fraction that volatilizes as NH3 and NOX for organic fertilizers; t NH3-N and NOX-N (t N)-1




As noted in GPG 2000, the default emission factor (EF1) is 1.25 % of applied N, and this value should be used when country-specific factors are unavailable. The default values for the fractions of synthetic and organic fertilizer nitrogen that are emitted as NOX and NH3 are 0.1 and 0.2 respectively in 2006 IPCC Guidelines. Project participants may use scientifically established specific emission factors that are more appropriate for their project. Specific good practice guidance on how to derive specific emission factors is given in Box 4.1 of GPG 2000.

7. Leakage

Leakage (LK) represents the increase in GHGs emissions by sources which occurs outside the boundary of an A/R CDM project activity which is measurable and attributable to the A/R CDM project activity. According to the guidance provided by the Executive Board, leakage also includes the decrease in carbon stocks which occurs outside the boundary of an A/R CDM project activity which is measurable and attributable to the A/R CDM project activity (see EB 22, Annex 15).


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There are four sources of the leakage covered by this methodology (Table 9):

• GHG emissions caused by vehicle fossil fuel combustion due to transportation of seedling, labour, staff and harvest products to and/or from project sites;

• GHG emissions caused by displacement of people. These people have no influence over pre-project land use, and therefore do not fall under the activity displacement leakage [e.g., these people could be employees];

• Carbon stock decreases caused by displacement of pre-project grazing;

• Displacement of fuelwood collection and charcoal production from inside to outside the project boundary;

• Increased use of wood posts for fencing.

Table 9: Emissions sources included in or excluded from leakage

Sources Gas Included/ excluded

Justification / Explanation of choice

CO2 Included Significant source of leakage CH4 Excluded Insignificant source of leakage

Combustion of fossil fuels by vehicles N2O Excluded Insignificant source of leakage

CO2 Included Significant source of leakage CH4 Excluded Not significant Displacement of

people N2O Excluded Not significant CO2 ExcludedI

ncluded Significant source of leakage Will not occur according to applicability conditions

CH4 Excluded Not significant

Displacement of pre-project grazing and agricultural activities N2O Excluded Not significant

CO2 Included Decrease in carbon stocks outside the project boundary CH4 Excluded Not applicable

Activity displacement: fuelwood collection

N2O Excluded Not applicable

CO2 Included Decrease in carbon stocks outside the project boundary CH4 Excluded Not applicable

Increased use of wood posts for fencing N2O Excluded Not applicable

Total leakage is quantified as follows:

LK = LKVehicle + LKPeopleDiscplacement + LKConversion + LK fuel-wood + LKfencing (B.47)

where:

LK Total leakage up to year t*; t CO2-e

LKPeopleDisplacement Total leakage due to deforestation due to people displacement

LKConversion Leakage due to conversion of land to grazing land up to year t*; t CO2-e

LKVehicle Total GHG emissions due to fossil fuel combustion from vehicles up to year t*; t CO2-e

LK fuel-wood Leakage due to displacement of fuel-wood collection up to year t*; t CO2-e

LKfencing Leakage due to increased use of wood posts for fencing up to year t*; t CO2-e


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Note: In this methodology, Equation (B.47) is used to estimate leakage for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated.

7.1. Estimation of LKVehicle (leakage due to fossil fuel consumption)

Leakage due to fossil fuel consumption shall be calculated using the A/R Methodological Tool for “Estimation of GHG emissions related to fossil fuel combustion in A/R CDM project activities” where:

∑=

=*

1,

t

yyFCVehicle ETLK * 1 year (B.48)

2,COVehicleVehicle LKLK = (B.51)

∑∑∑=

⋅=*

1, )(

2

t

txyt

x yxyCOVehicle mptionFuelConsuEFLK (B.52)

xytxytxytxyt eknptionFuelConsum ⋅⋅= (B.53)

where:

LKVehicle Total GHG emissions due to fossil fuel combustion from vehicles; t CO2-e yr-1



LKVehicle,CO2 CO2 emissions due to fossil fuel combustion from vehicles; t CO2-e yr-1

x Vehicle type

y Fuel type


FuelConsumptionxyt Recorded consumption of fuel type y of vehicle type x at time t; liters


kxyt Kilometers traveled by each of vehicle type x with fuel type y at time t; km


1, 2, 3, … t* years elapsed since the start of the A/R CDM project activity

Country-specific emission factors shall be used. There are three possible sources of emission factors:

• National emission factors: These emission factors may be developed by national programmes such as national GHGs inventory;

• Regional emission factors;



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Project participants shall make conservative and credible assumptions of yearly fuel consumption taking into account travel distances, vehicle/machine fuel efficiency, machine hours, and timing of planting and harvesting. Whenever possible, the assumptions shall be supported by verifiable evidence.

7.2. Estimation of LKPeopleDisplacement (leakage caused by displacement of people that have no influence over pre-project land use, and therefore do not fall under the activity displacement leakage)

By terminating a current land use, the A/R CDM activity may cause the loss of employment, and therefore cause the displacement of former employees. People displacement leakage may occur in the years immediately after employees are made redundant, when these individuals displaced by the project re-establish their livelihoods. This leakage does not necessarily occur immediately after the start of the project activity, since the project’s planting activities may provide initial employment.

If employment is lost, some of the displaced employees and their households may decide to establish a farm as their new livelihood. Establishment of new farms may potentially lead to deforestation. Where forest loss occurs through the actions of the displaced households a leakage debit will be taken by the project.

People displacement leakage is fundamentally different from activity shifting leakage, since the displaced people do not have a direct link with the pre-project land use. Conversely, activity shifting leakage is a situation where land use activities that are taking place on the project lands are continued elsewhere after project initiation, either because those responsible for the land use activities are displaced (i.e. farmers, cattle ranchers) or because third persons take up the land use activity elsewhere to fill a market gap left by the activities ceased by the project.

Step 1: Record the number of employees that the pre-project land uses sustain.

Step 2: Assume for the ex ante estimation that all of these jobs will be lost and that all the households move away.

Step 3: Project proponents shall estimate the likelihood that a household that moves establishes a new farm based on an analysis of trends for rural-rural and rural-urban migration in the region or the country. Sources for estimating migration trends include official data (e.g., regional or national demographic censuses) and expert opinions. In order to be conservative, all displacement of workers is assumed to lead to a move and all rural-rural migration is assumed to lead to colonization (i.e. new farm establishment and not new wage employment elsewhere). (For instance, the project proponents shall assume that 3 households establish a new farm, if 5 jobs will be lost and if national census reports indicate that 60% of internal migration originating from rural areas involves moves to other rural areas, rather than moves to cities.)

Step 4: Project proponents shall present transparent and verifiable information regarding the average area of smallholder farms in the region.

Step 5: Calculate the total leakage of all households according to the following formula:

LKPeopleDisplacement = NDH · AD · FS (B.54)

AD = ASF (B.55)


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where:

LKPeopleDisplacement Total leakage due to deforestation due to people displacement; t CO2-e

NDH Number of employees that are deemed likely to establish a new farm; dimensionless

AD Area deforested by each displaced household; ha

ASF Average size of small-holder farms in the larger project area; ha

FS Mean carbon stock of primary forests according to the GPG-LULUCF, Table 3A 1.4, pages 3.159-3.162; t CO2-e ha-1

7.2. Estimation of LKConversion (leakage due to carbon stock decreases caused by displacement of pre-project grazing)

Demonstrate that leakage from activity displacement due to displacement of pre-project grazing activities does not occur

Leakage due to carbon stock decreases caused by displacement of pre-project grazing (conversion of land to grazing land - LKConversion) shall be calculated using the latest version of the A/R methodological tool: “Estimation of GHG emissions related to displacement of grazing activities in A/R CDM project activity” where LKConversion shall be calculated using the parameter LKDisplacement,t (Leakage due to the displacement of animals in year t) as provided by the tool:

∑=

=*

1,

t

ttntDisplacemeConversion LKLK (B.49)

where:

LKConversion Leakage due to carbon stock decreases caused by displacement of pre-project grazing; t CO2-e

LKDisplacement,t Leakage due to the displacement of animals in year t; t CO2-e


Following applicability condition 13, this methodology only applies for a specific project if the project proponents can demonstrate that the livestock are not displaced somewhere else, but slaughtered or sold to be slaughtered. The project proponents shall provide evidence of what happened to the livestock at the initial verification.

It needs to be demonstrated that there are sufficient areas where the land is used below its sustainable capacity in the vicinity to the project area, within the same market area (“project region”). Therefore, it is not expected that any stocked areas will need to be converted to grazing land or to cropland.

For the purpose of demonstrating that market effects would not trigger conversion of stocked areas to grazing land or cropland, the project region is understood as the region that delivers to the same regional markets for products from the grazing and agricultural land uses on the project sites identified below in Step 1. The project proponents shall define the project region based on past practices of selling products from the project lands, and/or based on interviews with the local population.


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Sustainable land-use capacity of agricultural land and sustainable carrying capacity of lands shall be determined based on the following possible data sources24: interviews with animal owners, a Participatory Rural Appraisal (PRA), local or regional animal census data, land-use census data, interviews with local experts, scientific sources, IPCC default values.

In order to compare the un-used land-use capacity to the required capacity, follow the procedure in Steps 3-6 for pasture land use and in Steps 7-8 for agricultural land use:

Step 1: Before planting, collect data on the pre-project land uses on the project sites:

(a) Record the total number of pre-project animal units in the project boundary. This is the total need for displacement of pre-project grazing activities to outside the project boundary within the project region.

(b) Record the total area of pre-project agricultural activities in the project boundary. This is the total need for area for displacement of pre-project agricultural activities to outside the project boundary within the project region.

Step 2: Collect data on the land-use situation in the project region outside the project boundary. Record the total area of pre-project existing pastures in the project region outside the project boundary:

(a) Record the average cattle stocking rates on pre-project existing pastures in the project region outside the project boundary.

(b) Record the average carrying capacity of the total area under pre-project existing pasture in the project region outside the project boundary.

(c) Record the area of pre-project abandoned lands available in the project region outside the project boundary that are not regenerating.

(d) Determine the average carrying capacity of the abandoned lands identified in step 2d. Determine the area of these abandoned lands that are suitable for sustaining the pre-project agricultural land uses.

Step 3: Derive the unused carrying capacity on existing pastures, available for absorbing the displacement of pre-project grazing activities from inside the project boundary to outside the project boundary within the project region. In doing so, the unused carrying capacity corresponds to the difference between the average cattle stocking rates (from Step 2b) and the average carrying capacity (from Step 2c), multiplied by the area being used for pasture land-use activities outside the project boundary (from Step 2a).

Step 4: Check whether there is sufficient un-used carrying capacity available on existing pastures for displacement of pre-project grazing activities (comparing the un-used carrying capacities in Step 3 to the need for carrying capacity from Step 1a). If not, consider Step 5.

Step 5: Derive the total carrying capacity on abandoned lands that are not regenerating, available for absorbing the displacement of pre-project grazing activities from inside the project boundary to outside the project boundary within the project region. In doing so, the total carrying capacity available on abandoned lands that are not regenerating corresponds to the product of those areas (as determined in Step 2d) and the average carrying capacity on those areas (from Step 2e).

Step 6: Check whether there is sufficient carrying capacity on abandoned lands that are not regenerating, available for absorbing the displacement of pre-project grazing activities (comparing the un-used 24 This methodology does not consider increasing land-use capacity by using fertilizers. If a project wants to

consider increased use of fertilizers, an amendment shall be proposed.


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carrying capacities in Step 5 to the remaining need for carrying capacity after Step 4). If not, this methodology is not applicable.

Step 7: Derive the total area of abandoned lands that are not regenerating and that will not be occupied by the displacement of the pre-project grazing activities, available for absorbing the displacement of pre-project agricultural activities. In doing so, the areas available are the remainder after Step 6, if they are suitable to support the agricultural activities that occur inside the project boundary in a sustainable way (as determined in step 2e).

Step 8: Check whether there are sufficient areas on abandoned lands that are not regenerating available for absorbing the displacement of pre-project agricultural activities (comparing the un-used areas in Step 7 to the need for areas from Step 1b). If not, this methodology is not applicable.

7.3. Estimation of LK fuel-wood (Leakage due to displacement of fuel-wood collection)

Depending on the specific project circumstance, all pre-project fuel-wood collection activities (including in-site charcoal production), or a fraction of them, may have to be displaced permanently, or temporarily, outside the project boundary. Where pre-project fuel-wood collection and/or charcoal production activities exist, it is necessary to estimate the pre-project consumption of fuel-wood in randomly selected different discrete parcels or sub-areas within the project area. This can be done by interviewing households or implementing a Participatory Rural Appraisal (PRA). Where several discrete parcels are present in the project area, sampling techniques can be used. Others sources of information, such as local studies on fuel-wood consumption and/or charcoal production may also be used. Average data from the 5 to 10 years time period preceding the starting date of the A/R CDM project activity should be used whenever possible.

PAfw

BLBL SFR

sFGFG = (B.50)

where:

FGBL Average pre-project annual volume of fuel-wood gathering in the project area; m3 yr-1

sFGBL Sampled average pre-project annual volume of fuel-wood gathering in the project area; m3 yr-1

SFRPAfw Fraction of total area or households in the project area sampled; dimensionless

The methodology assumes that the estimated historical or current fuel-wood consumption and/or charcoal production (FGBL) will remain constant over the entire crediting period. Based on the planned afforestation or reforestation establishment schedule and the prescribed management, the periods of time from which fuel-wood collection and/or charcoal production should be excluded from the considered sample discrete areas as well as the amounts of fuel-wood produced in the different stands through thinning, coppicing and harvesting can be specified. This planning should be used to estimate the amount of fuel-wood and/or charcoal that may have to be obtained each year from sources outside the project boundary.

tARBLtoutside FGFGFG ,, −= (B.51)


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where:

FGoutside,t Volume of fuel-wood gathering displaced outside the project area at year t; m3 yr-1

FGBL Average pre-project annual volume of fuel-wood gathering in the project area; m3 yr-1

FGAR,t Volume of fuel-wood gathering allowed/planned in the project area under the proposed A/R CDM project activity; m3 yr-1

Leakage due to displacement of fuel-wood collection can be set as zero (LK fuel-wood = 0) under the following circumstances:

• FGBL < FGAR,t;

• LK fuel-wood < 2% of actual net GHG removals by sinks (See EB 22, Annex 15).

In all other cases, leakage due to displacement of fuel-wood collection shall be estimated as follow (IPCC GPG-LULUCF - Equation 3.2.8):

LKfuel-wood = ∑=

*

1

t

t

FGt · D · R · CF · MWCO2-C *1 year (B.52)

FGt = FGoutside,t (B.53)

where:


FGt Volume of fuel-wood gathering displaced in unidentified areas; m3 yr-1


D Average basic wood density (see IPCC GPG-LULUCF, Table 3A.1.9); t d.m. m-3

CF Carbon fraction of dry matter biomass (default = 0.5); t C (t d.m.)-1

R Root-shoot ratio; dimensionless



7.4. Estimation of LKfencing (Leakage due to increased use of wood posts for fencing)

The protection of natural regeneration and planted trees from animal grazing and fuel-wood collection may require fencing using wood posts. Where the wood posts are not obtained from sources inside the project area, they may have to be supplied from outside sources. If these outside sources are not renewable (e.g. the production of posts leads to forest degradation, deforestation or devegetation), leakage may occur. The supply source of the posts used for fencing should be specified in the PDD. If the outside source used is not renewable, leakage due to increased use of wood posts for fencing shall be estimated as follow:

∑=

⋅=*

1

t

t

tfencing FNRP

DBPPARLK ⋅⋅⋅⋅⋅ CFBEFDAPV 2 MWCO2-C (B.54)


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where:


PARt Perimeter of the areas to be fenced at year t; m

DBP Average distance between wood posts; m

FNRP Fraction of posts from off-site non-renewable sources; dimensionless

APV Average volume of wood posts (estimated from sampling); m3

D Average basic wood density; t d.m. m-3 (See IPCC GPG-LULUCF, 2003 Table 3A.1.9)

BEF2 Biomass expansion factor for converting volumes of extracted round wood to total above-ground biomass (including bark); dimensionless Table 3A.1.10

CF Carbon fraction of dry matter biomass (default = 0.5); t C (t d.m.)-1



Note: As per the guidance provided by the Executive Board (See EB 22, Annex 15) leakage due to increased use of wood posts for fencing can be excluded from the calculation of leakages under the following circumstance:

• LKfencing < 2% of actual net GHG removals by sinks (See EB 22, Annex 15).

8. Ex ante net anthropogenic GHG removal by sinks

The net anthropogenic GHG removals by sinks is the actual net GHG removals by sinks minus the baseline net GHG removals by sinks minus leakage, therefore, the following general formula can be used to calculate the net anthropogenic GHG removals by sinks of an A/R CDM project activity (CAR-CDM), in t CO2-e.

LKCCC BSLACTUALCDMAR −−=− (B.55)

where:

CAR-CDM Net anthropogenic greenhouse gas removals by sinks; t CO2-e


CBSL Baseline net greenhouse gas removals by sinks; t CO2-e

LK Leakage up to year t* ; t CO2-e

Note: In this methodology, Equation (B.55) is used to estimate net anthropogenic GHG removals by sinks for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated. This is done because project emissions and leakage are permanent, which requires to calculate their cumulative values since the starting date of the A/R CDM project activity.


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Calculation of tCERs and lCERs

To estimate the amount of CERs that can be issued at time t*= t2 (the date of verification) for the monitoring period T = t2 – t1, this methodology uses the EB approved equations,25 which produce the same estimates as the following:

tCERs = CAR-CDM,t2 (B.56)

lCERs = CAR-CDM,t2 - CAR-CDM,t1 (B.57)

where:

tCERs Number of units of t Temporary Certified Emission Reductions; t CO2-e

lCERs Number of units of l Long-term Certified Emission Reductions; t CO2-e

CAR-CDM,t2 Net anthropogenic greenhouse gas removals by sinks, as estimated for t* = t2; t CO2-e


9. Uncertainties

The approach provided in Section III.11 should be applied.

25 See EB 22, Annex 15 (http://cdm.unfccc.int/EB/Meetings/022/eb22_repan15.pdf)


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10. Data needed for ex ante estimations

Data / Parameter Unit Description Vintage Data sources and geographical scale

Historical land use/cover data

Dimensionless Determining baseline approach

Demonstrating eligibility of land

Dimensionless Earliest possible up to now Publications, national or regional forestry inventory, local government, interview

Land use/cover map Dimensionless Demonstrating eligibility of land, stratifying land area

Reforestation: ~1990. Afforestation: 50 years prior to project start and the most recent date.

Forestry inventory

Satellite image Dimensionless Demonstrating eligibility of land, stratifying land area

Reforestation: ~1990. Afforestation: 50 years prior to project start and the most recent date

e.g. Landsat

Landform map Dimensionless Stratifying land area Most recent date Local government Soil map Dimensionless Stratifying land area Most recent date Local government

and institutional agencies

National and sectoral policies

Dimensionless Additionality consideration Before 1998

UNFCCC COP/MOP decisions

Dimensionless 1997 up to now UNFCCC website

IRR, NPV, unit cost of service

Dimensionless Indicators of investment analysis

Most recent data Calculation (if any, depends on the way of additionality analysis)

Investment costs Dimensionless Including land purchase or rental, machinery, equipments, buildings, fences, site and soil preparation, seedling, planting, weeding, pesticides, fertilization, supervision, training, technical consultation, etc. that occur in the establishment period

Most recent date, taking into account market risk

Local statistics, published data and/or survey (if any, depends on the way of additionality analysis)


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Operations and maintenance costs

Dimensionless Including costs of thinning, pruning, harvesting, replanting, fuel, transportation, repairs, fire and disease control, patrolling, administration, etc.


Local statistics, published data and/or survey (if any, depends on the way of additionality analysis)

Transaction costs Dimensionless Including costs of project preparation, validation, registration, monitoring, etc.

Most recent date DOE

Revenues Dimensionless Revenues from timber, fuel-wood, non-wood products, with and without CER revenues, etc.


Local statistics, published data and/or survey (if any, depends on the way of additionality analysis

0.001 kg t-1 Conversion from kg to tones of CO2

IPCC. Global default

ERatN2O Dimension-less IPCC default emission ratio for N2O (0.007);


ERatCH4 Dimensionless IPCC default emission ratio for CH4 (0.012)


MWCH4-C t CH4 (t C)-1 Ratio of molecular weights of CH4 and C (16/12)


MWN2O-N t N2O (t N)-1 Ratio of molecular weights of N2O and N (44/28)


MWCO2-C t CO2 (t C)-1 Ratio of molecular weights of CO2 and C (44/12)


GWPCH4 t CO2-e (t CH4)-

1 Global Warming Potential for CH4 (21 for the first commitment period)


GWPN2O t CO2-e (t N2O)-1

Global Warming Potential for N2O (310 for the first commitment period)


Aburn,i hayr-1 Area of slash and burn for stratum i

Estimated ex ante, monitored ex post

AD ha Area deforested by each displaced household

Monitored ex post or assumed

Adistijt ha yr-1 Forest areas affected by disturbances in stratum i, species j, time t

Most updated Estimated ex ante, monitored ex post. Stratum and species

AdistijT ha-1 yr-1 Average annual area affected by disturbances for stratum i, species j, during the period T

Most updated Estimated ex ante

Ai ha Area of stratum i Most updated Estimated ex ante Aijt ha Area of stratum i, species j, at

time t Most updated Estimated ex ante

ARemain ijt ha Area of the land-use type j that is expected to remain, in stratum i, between the year t=tx and t=tx+1

Estimated ex ante


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AChange ijt ha Area of the land-use type j that is expected to change, in stratum i, between the year t=tx and t=tx+1

Estimated ex ante

AijT ha yr-1 Average annual area for stratum i, species j, during the period T

Most updated Estimated ex ante

APV m3 Average volume of wood posts

Estimated from sampling

ASF ha Average size of small-holder farms in the larger project area

Estimated ex ante

BEF1,j Dimensionless Biomass expansion factor for conversion of annual net increment (including bark) in merchantable volume to total above-ground biomass increment for species j

GPG-LULUCF, national GHG inventory, local survey

BEF2 Dimensionless Biomass expansion factor for converting volumes of extracted round wood to total above-ground biomass (including bark)

Table 3A.1.10

BEF2,j Dimensionless Biomass expansion factor for converting merchantable volumes of extracted roundwood to total aboveground biomass (including bark) for species j


Bi t d.m. ha-1 Average stock in above-ground living biomass before burning for stratum i


Bnon-tree, it t d.m. ha-1 Average non-tree biomass stock on land to be planted before the start of a proposed A/R CDM project activity for stratum i, time t

Estimated ex ante

Bpre,ijt t d.m. ha-1 Average pre-existing stock of pre-project biomass in the tree and non-tree living biomass, deadwood and litter carbon pools on land to be planted before the start of a proposed A/R CDM project activity for baseline stratum i, species j, time t

Bw, ijt t d.m. ha-1 Average above-ground biomass stock for stratum i, species j, time t



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CAB,ijt t C Carbon stock in above-ground biomass for stratum i, species j, at time t

Calculated. Local and species specific

CACTUAL t CO2-e Actual net greenhouse gas removals by sinks

Calculated. Project specific

CBB,ijt t C Carbon stock in below-ground biomass for stratum i, species j, at time t

Calculated. Local and species specific

CBSL t CO2-e Baseline net greenhouse gas removals by sinks

Calculated

CDW ijt1 t C Total carbon stock in deadwood for stratum i, species j, calculated at time t=t1

Calculated


Calculated

CDWij,t-1 t CO2-e Carbon stock in the deadwood carbon pool in stratum i, species j, time t = t-1-1 year

Calculated

CE Dimensionless Combustion efficiency (IPCC default =0.5)

IPCC GPG-2000, national GHG inventory. Global and national default

CF t C (t d.m)-1 Carbon fraction of dry biomass

Default = 0.5

CFj t C (t d.m)-1 Carbon fraction of dry matter for species j


CFnon-tree t C (t d.m.)-1 Carbon fraction of dry biomass in non-tree vegetation


CFpre t C (t d.m.)-1 Carbon fraction of dry biomass in pre-existing vegetation


C DW ijt1 t C Total carbon stock in deadwood for stratum i, species j, calculated at time t=t1

CLB ijt t C Total carbon stock in living biomass of trees for stratum i, species j, at time t


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CLB ijt1 t C Total carbon stock in living biomass of trees for stratum i, species j, calculated at time t=t1 Average annual carbon stock change in living biomass of trees

Calculated

CLB ijt2 t C Total carbon stock in living biomass of trees for stratum i, species j, calculated at time t=t2

Calculated

CLI ijt1 t C Total carbon stock in litter for stratum i, species j, calculated at time t=t1

Calculated

CLI ijt2 t C Total carbon stock in litter for stratum i, species j, calculated at time t=t2

Calculated

D t d.m. m-3 Average basic wood density See IPCC GPG-LULUCF, Table 3A.1.9

DBHt cm Mean diameter at breast height at time t

Estimated

DC yr-1 Dimension-less

Decomposition rate (% (fraction of carbon stock in total deadwood stock decomposed annually)

GPG-LULUCF, national and local forestry inventory, preferably investigated ex post

Dj t d.m. m-3 Basic wood density for species j


DBP m Average distance between wood posts


Dwj t d.m. m-3

merchantable volume

Intermediate deadwood density for species j


EBiomassBurn, CH4 t CO2-e yr-1 CH4 emission from biomass burning in slash and burn

Calculated

EBiomassBurn, N2O t CO2-e yr-1 N2O emission from biomass burning in slash and burn

Calculated.

EBiomassBurn,C t C yr-1 Loss of carbon stock in aboveground biomass due to slash and burn

Calculated

Ebiomassloss t CO2-e Decrease in the carbon stock in the tree and non-tree living biomass, deadwood and litter carbon pools of pre-existing vegetation in the year of site preparation up to time t*

Calculated

EF1 t N2O-N (t N input)-1

Emission Factor for emissions from N inputs

GPG 2001. Global default


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EFuelBurn t CO2-eyr-1 Total GHG emissions due to fossil fuel combustion from vehicles

Calculated

EFxy Dimension-less CO2 emission factor for vehicle type x with fuel type y

GPG-2000, 2006 IPCC Guideline, national GHG inventory

ENon-CO2, BiomassBurn t CO2-e yr-1 Increase in Nonnon-CO2 emission as a result of biomass burning within the project boundary


ETFC,y t CO2 CO2 emissions from fossil fuel combustion during the year y

Calculated

exyt Liters km-1 Fuel efficiency of vehicle type x with fuel type y at time t

GPG-2000, 2006 IPCC Guideline, national GHG inventory

EVehicle,CO2 t CO2-e yr-1 Total CO2 emissions due to fossil fuel combustion from vehicles

Calculated

FGAR,t m3 yr-1 Volume of fuel-wood gathering allowed/planned in the project area under the proposed A/R CDM project activity

Calculated

FGBL m3 yr-1 Average pre-project annual volume of fuel-wood gathering in the project area

Calculated

FGijt m3 yr-1 Annual volume of fuel wood harvesting of living trees for stratum i, species j, time t


FGijT m3 ha-1 yr-1 Average annual volume of fuel wood harvested for stratum i, species j, during the period T


FGoutside,t m3 yr-1 Volume of fuel-wood gathering displaced outside the project area at year t

Calculated

FGt m3 yr-1 Volume of fuel-wood gathering displaced in unidentified areas

Calculated

FNRP Dimensionless Fraction of posts from off-site non-renewable sources

Estimated

fj(DBHt,Ht) t d.m. Dimension-less

Allometric equation linking above-ground biomass of a tree (t d.m.ha-1) to mean diameter at breast height (DBH) and possibly mean tree height (H) for species j

Forestry inventory, published data, local survey

FON t t N Amount of organic fertilizer nitrogen applied at time t adjusted for volatilization as NH3 and NOX

Estimated


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FracGASF t NH3-N and NOX-N (t N)-1

Fraction that volatilises as NH3 and NOX for synthetic fertilizers

IPCC Guideline. Global default

FracGASM t NH3-N and NOX-N (t N)-1

Fraction that volatilises as NH3 and NOX for organic fertilizers

IPCC Guideline. Global default

FS CO2-e ha-1 Mean carbon stock of forest vegetation in the larger project

GPG-LULUCF, national and local forestry inventory.

FSN t t N Amount of synthetic fertilizer nitrogen applied at time t adjusted for volatilization as NH3 and NOX

Estimated to measured ex ante, measured ex post

FuelConsumptionxyt Liters Recorded consumption of fuel type y of vehicle type x at time t


Fwfijt yr-1

dimension-less Fraction of annually harvested deadwood carbon stock harvested as fuel wood for stratum i, species j, time t


GHGE t CO2-e yr-1 GHG emissions as a result of the implementation of the A/R CDM project activity within the project boundary

Calculated

GTOTAL,ij t d.m ha-1 yr-1 Annual average increment rate in total biomass in units of dry matter for stratum i, species j

Most recent GPG-LULUCF, national and local forestry inventory

Gw,ijt t d.m ha-1 yr-1 Average annual above-ground dry biomass increment of living trees for stratum i, species j at time t

GPG-LULUCF, national and local forestry inventory

Hfijt Dimension-less Fraction of annually harvested merchantable volume not extracted and left on the ground as harvesting residue for stratum i, species j, time t


Hijt m3 ha-1 yr-1 Annually extracted merchantable volume for stratum i, species j, time t


HijT m3 ha-1 yr-1 Average annually harvested merchantable volume for stratum i, species j during the period T Average annual net increment in merchantable volume for stratum i, species j during the period T


Ht m Mean t Tree height at time t Estimated ex ante, monitored ex post

i Dimension-less 1, 2, 3, … mBL baseline strata Estimated ex ante, monitored ex post

Iv,ijt m3 ha-1 yr-1 Average annual increment in merchantable volume for stratum i species j at time t

Estimated ex ante


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Iv,ijT m3 ha-1 yr-1 Average annual net increment in merchantable volume for stratum i, species j during the period T

Estimated ex ante

j Dimension-less 1, 2, 3, … sBL baseline tree species


kxyt km Kilometers traveled by each of vehicle type y with fuel type x at time t


Lfw, ijt CO2-e yr-1 Annual carbon loss due to fuel wood gathering for stratum stratum i, species j, time t


Lhr, ijt t CO2-e yr-1 Annual carbon loss due to commercial harvesting for stratum i, species j, time t


LK t CO2-e Total leakage up to year t* Leakage

Calculated

LKConversion t CO2-e Leakage due to conversion of land to grazing land up to year t*

Calculated

LKfencing t CO2-e Leakage due to increased use of wood posts for fencing up to year t*

Calculated

LK fuel-wood t CO2-e Leakage due to displacement of fuel-wood collection up to year t*

Calculated

LKPeople Displacement t CO2-e Total carbon stock decreases outside the project boundary due to forest loss attributable to displacement of people

Calculated

LKVehicle t CO2-e yr-1 Total GHG emissions due to fossil fuel combustion from vehicles up to year t*

Calculated

LKVehicle,CO2 t CO2-e yr-1 Total CO2 emissions due to fossil fuel combustion from vehicles

Calculated

Lot, ijt CO2-e yr-1 Annual natural losses (mortality) of carbon for stratum stratum i, species j, time t

Calculated

MfijT Dimensionless Mortality factor = fraction of Vijt1 died during the period T

Estimated

Mfijt Dimensionless Mortality factor = fraction of Vijt dying at time t

Estimated

N2Odirect-Nfertilizer t CO2-e yr-1 The Increase in the direct N2O emission as a result of nitrogen application within the project boundary

Estimated

N/C ratio t N (t C)-1 Nitrogen-Carbon ratio; IPCC. Global default

NDH Dimension-less Number of employees that are deemed likely to establish a new farm



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NON-Fert t t N Amount of organic fertilizer nitrogen applied at time t


NSN-Fert t t N Amount of synthetic fertilizer nitrogen applied at time t

Estimated ex ante

nTRijt ha-1 Number of trees in stratum i, species j, at time t


nxyt Number of vehicles Estimated ex ante PARt m Perimeter of the areas to be

fenced at year t Estimated ex ante

tCERs t CO2-e Dimension-less

Number of units of t Temporary Certified Emission Reductions

Estimated ex ante

lCERs t CO2-e Dimension-less

Number of units of l Long-term Certified Emission Reductions

Estimated ex ante

CAR-CDM t CO2-e Net anthropogenic greenhouse gas removals by sinks

Estimated ex ante

CAR-CDM,t2 t CO2-e Net anthropogenic greenhouse gas removals by sinks, as estimated for t* = t2

Estimated ex ante

CAR-CDM,t1 t CO2-e Net anthropogenic greenhouse gas removals by sinks, as estimated for t* = t1

Estimated ex ante

R Dimensionless Root-shoot ratio IPCC GPG, national GHG inventory. Global or national default

Rj Dimension-less Root-shoot ratio appropriate to increments for species j

IPCC GPG-2000, national GHG inventory. Global and or national default

SFGBL m3 yr-1 Sampled average pre-project annual volume of fuel-wood gathering in the project area

SFRPAfw Dimension-less Fraction of total area or households in the project area sampled

t Years 1, 2, 3, …t* years elapsed since the start of the A/R CDM project activity

tx Year Starting year of a land-use change

T Years Number of years between times t2 and t1 (T = t2-t1)


Vijt m3 ha-1 Average merchantable volume of stratum i, species j, at time t

Forestry inventory, yield table, local survey. Local and species specific.


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Vijt1 m3 ha-1 Average merchantable volume of stratum i, species j, at time t = t1

Forestry inventory

Vijt2 m3 ha-1 Average merchantable volume of stratum i, species j, at time t = t2

Forestry inventory

x Dimension-less Vehicle type Estimated ex ante, monitored ex post

y Dimension-less Fuel type Estimated ex ante, monitored ex post

∆CChange t CO2-e Sum of the carbon-stock changes in all biomass pools from land uses that change

Calculated

∆CRemain t CO2-e Sum of the changes in the stocks of all biomass pools from land uses that remain

Calculated

Cincrease ijt t C DeIncreases in carbon stock in all biomass pools due to deincreasing areas for stratum i, species j, calculated at time t

Calculated

Cdecrease ijt t C InDecreases in carbon stock in all biomass pools due to indecreasing areas for stratum i, species j, at time t

Calculated

AChange ijt ha Area of a land-use type j expected to change between a given year t and the subsequent year t+1 in stratum i

Estimated

Bijt t d.m. ha-1 Average biomass stock on land before or after the land-use change for stratum i, species j, time t

Estimated

∆CdescDW ijt t CO2-e yr-1 Annual decrease of carbon stock in the deadwood carbon pool due to deadwood decomposition for stratum i, species j, time t

Calculated

∆CdescLI ijt t CO2-e yr-1 Annual decrease of carbon stock in the litter carbon pool due to litter decomposition for stratum i, species j, time t

Calculated

∆CDW t CO2-e Sum of the changes in deadwood carbon stocks

Calculated

∆CDW ijt t CO2-e yr-1 Annual carbon stock change in deadwood for stratum i, species j, time t

Calculated

∆CfwDW ijt t CO2-e yr-1 Annual decrease of carbon stock in the deadwood carbon pool due to harvesting of deadwood for stratum i, species j, time t



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∆CfwLI ijt t CO2-e yr-1 Annual decrease of carbon stock in the litter carbon pool due to harvesting of litter for stratum i, species j, time t


∆CG, ijt t CO2-e yr-1 Annual increase in carbon stock due to biomass growth for stratum i, species j, time t


∆ChrDW ijt t CO2-e yr-1 Annual increase of carbon stock in the deadwood carbon pool due to harvesting residues not collected for stratum i, species j, time t


∆ChrLI ijt t CO2-e yr-1 Annual increase of carbon stock in the litter carbon pool due to in harvesting residues not collected remaining on site for stratum i, species j, time t


∆CL, ijt t CO2-e yr-1 Annual decrease in carbon stock due to biomass loss for stratum i, species j, time t


∆CLB t CO2-e Sum of the changes in living biomass carbon stocks (above- and below-ground)

Calculated

∆CLB ijt t CO2-e yr-1 Annual carbon stock change in living biomass for stratum i, species j, time t

Calculated

∆CLI t CO2-e Sum of the changes in litter carbon stocks

Calculated

∆CLI ijt t CO2-e yr-1 Annual carbon stock change in litter for stratum i, species j, time t

Calculated

∆CmlbDW ijt t CO2-e yr-1 Annual increase of carbon stock in the deadwood carbon pool due to mortality of the living biomass for stratum i, species j, time t


∆CmlbLI ijt t CO2-e yr-1 Annual increase of carbon stock in the litter carbon pool due to mortality of the living biomass for stratum i, species j, time t

Calculated

11. Other information

The baseline net GHG removal by sinks, actual net GHG removal by sinks and net anthropogenic GHG removal by sinks are expressed annually since not all emission/removals occur every year. Some sources such as fertilizer application, machinery usage and slash and burn occur only in selected years. The annual carbon stock change is calculated in the timeframe of a monitoring interval followed by dividing by the year of the interval. Hence at the end, all source/sinks are expressed in annual numbers. Since CERs will not be issued annually, the issued tCERs or lCERs will be calculated according to equations made available in the chapter: Ways of calculating tCERs and lCERs.


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Section III: Monitoring methodology description

1. Monitoring project boundary and project implementation

Monitoring of project implementation includes:

• Monitoring of the project boundary;

• Monitoring of forest establishment;

• Monitoring of forest management.

The corresponding methodology procedures are outlined below.

(a) Monitoring of the boundary of the proposed A/R CDM project activity

This is meant to demonstrate that the actual area afforested or reforested conforms with the afforestation or reforestation area outlined in the project plan. The following activities are foreseen:

• Field surveys concerning the actual project boundary within which A/R activity has occurred, site by site;

• Measuring geographical positions (latitude and longitude of each corner polygon sites) using GPS, analysis of geo-referenced spatial data, or other appropriate techniques;

• Checking whether the actual boundary is consistent with the description in the CDM-AR-PDD;

• Input the measured geographical positions into the GIS system and calculate the eligible area of each stratum and stand;

• The project boundary shall be monitored periodically all through the crediting period, including through remote sensing as applicable. If the forest area changes during the crediting period, for instance, because deforestation occurs on the project area, the specific location and area of the deforested land shall be identified. Similarly, if the planting on certain lands within the project boundary fails; these lands will be documented.

(b) Monitoring of forest establishment

To ensure that the planting quality conforms to the practice described in CDM—AR-PDD and is well-implemented, the following monitoring activities shall be conducted in the first three years after planting:

• Confirm that site and soil preparations are implemented based on practice documented in PDD. If pre-vegetation is removed, e.g., slash and burn of pre-existing vegetation, emissions associated shall be accounted for (described in section below).

• Survival checking:

o The initial survival rate of planted trees shall be counted three months after the planting, and re-planting shall be conducted if the survival rate is lower than 90 percent of the final planting density;

o Final checking three years after the planting;

o The checking of the survival rate may be conducted using permanent sample plots.


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• Weeding checking: check and confirm that the weeding practice is implemented as described in the PDD;

• Survey and check that species and planting for each stratum are in line with the PDD;

• Document and justify any deviation from the planned forest establishment.

(c) Monitoring of forest management

Forest management practices are important drivers of the GHG balance of the project, and thus must be monitored. Practices to be monitored include:

• Cleaning and site preparation measures: date, location, area, biomass removed and other measures undertaken;

• Planting: date, location, area, tree species;

• Fertilization: date, location, area, tree species, amount and type of fertilizer applied, etc.;

• Thinning: date, location, area, tree species, thinning intensity, volumes or biomass of trees removed;

• Harvesting: date, location, area, tree species, volumes or biomass of trees removed;

• Coppicing: date, location, area, tree species, volumes or biomass of trees removed;

• Fuel wood collection: date, location, area, tree species, volumes or biomass of trees removed;

• Checking and confirming that harvested lands are re-planted, re-sowed or coppiced as planned and/or as required by forest law;

• Checking and ensuring that good conditions exist for natural regeneration if harvested lands are allowed to regenerate naturally;

• Monitoring of disturbances: date, location, area (GPS, analysis of geo-referenced spatial data, or other appropriate techniques, tree species, type of disturbance, biomass lost, implemented corrective measures, change in the boundary of strata and stands.

2. Sampling design and stratification

The number and boundaries of the strata defined ex ante using the methodology procedure outlined in Section II.3 may change during the crediting period (ex post). For this reason, strata should be monitored periodically. If a change in the number and area of the project strata occurs, the sampling framework should be adjusted accordingly. The methodology procedures for monitoring strata and defining the sampling framework are outlined below.


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2.1. Monitoring of strata

Stratification of the project area into relatively homogeneous units can either increase the measuring precision without increasing the cost unduly, or reduce the cost without reducing measuring precision because of the lower variance within each homogeneous unit. Project participants should present in the CDM-AR-PDD an ex ante stratification of the project area using the methods outlined in Section II.2 and build a geo-referenced spatial data base in a GIS platform for each parameter used for stratification of the project area under the baseline and the project scenario. This geo-referenced spatial data base should be completed at the earliest stages of the implementation of the A/R CDM project activity. The DOE shall verify the achievement of this stratification and geo-referenced spatial data base at the first verification. The consistency of the actual boundary of the strata and stands as monitored in the field with the description in the CDM-AR-PDD shall be periodically monitored as the boundaries may change due to the following:

• Unexpected disturbances occurring during the crediting period (e.g. due to fire, pests or disease outbreaks), differently affecting separate parts of an originally homogeneous stratum or stand;

• Forest management (cleaning, planting, thinning, harvesting, coppicing, re-replanting) may be implemented at different intensities, dates and spatial locations than originally planned in the CDM-AR-PDD;

• Two different strata may be similar enough to allow their merging into one stratum.

If one of the above occurs, ex post stratification is required. The possible need for ex post stratification shall be evaluated at each monitoring event and changes in the strata should be reported to the DOE for verification. Monitoring of strata and stand boundaries shall be done using a Geographical Information System (GIS), which allows integrating data from different sources (including GPS coordinates and Remote Sensing data). The monitoring of strata and stand boundaries is critical for a transparent and verifiable monitoring of the variable Aijt (area of stratum i, species j, at time t), which is of outmost importance for an accurate and precise calculation of net anthropogenic GHG removals by sinks.

2.2. Sampling framework

The sampling framework, including sample size, plot size, plot shape and plot location should be specified in the CDM-AR-PDD.

2.2.1. Definition of the sample size and allocation among strata

Permanent sampling plots will be used for sampling over time to measure and monitor changes in carbon stocks. Permanent sample plots are generally regarded as statistically efficient in estimating changes in forest carbon stocks because typically there is high covariance between observations at successive sampling events. However, it should be ensured that the plots are treated in the same way as other lands within the project boundary, e.g., during site and soil preparation, weeding, fertilization, irrigation, thinning, etc., and should not be destroyed over the monitoring interval. Ideally, staff involved in management activities should not be aware of the location of monitoring plots. Where local markers are used, these should not be visible.

The number of sample plots is estimated as dependent on accuracy and costs.


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It is assumed that the following parameters are from pre-project estimates (e.g. results from a pilot study) or literature data:

A Total size of all strata, e.g. the total project area; ha

Ai Size of each stratum (= ∑∑

=

tcr

t

S

jijt

PS

A1

where tcr is the end of the crediting period); ha

AP Sample plot size; ha

sti Standard deviation for each stratum i; dimensionless

Ci Cost of establishment of a sample plot for each stratum i; e.g. US$

Q Approximate average value of the estimated quantity Q, (e.g. wood volume); e.g. m3 ha-1

p Desired level of precision (e.g. 10%); dimensionless

then:

APAN /= (M.1)

APAN ii = (M.2)

pQE ∗= (M.3)

where:

N Maximum possible number of sample plots in the project area; dimensionless

Ni Maximum possible number of sample plots in stratum i; dimensionless

A Total size of all strata, e.g. the total project area; ha

Ai Size of each stratum (= ∑∑

=

tcr

t

S

jijt

PS

A1

where tcr is the end of the crediting period); ha


E Allowable error; dimensionless


p Desired level of precision (e.g. 10%); dimensionless


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With the above information, the sample size (number of sample plots to be established and measured) can be estimated as follows:

( )∑

∑∑

=

==

+

=PS

PSPS

m

iii

ii

m

ii

m

iii

stNzEN

CstNCistNn

1

2

2

2

11

**

****

α

(M.4)

( )i

ii

m

iii

m

iiii

i CstN

stNzEN

CstNn

SP

PS

**

**

**

1

2

2

2

1

∑

∑

=

=

+

=

α

(M.5)

where:

n Sample size (total number of sample plots required) in the project area; dimensionless

ni Sample size for stratum i; dimensionless

N Maximum possible number of sample plots in the project area; dimensionless

E Allowable error; dimensionless

Ni Maximum possible number of sample plots in stratum i; dimensionless

i 1, 2, 3, … mSP project scenario (ex post) strata; dimensionless

zα/2 Value of the statistic z (normal probability density function), for α = 0.05 (implying a 95% confidence level); dimensionless

sti Standard deviation for each stratum i; dimensionless

Ci Cost of establishment of a sample plot for each stratum i; e.g. US$


When no information on costs is available or the costs may be assumed as constant for all strata, then:

( )∑

∑

=

=

⋅+

⋅

⋅

=PS

PS

m

iii

m

iii

stNzEN

stNn

1

2

2

2

2

1

α

(M.6)


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( )ii

m

iii

m

hii

i stN

stNzEN

stNn

PS

PS

⋅⋅

⋅+

⋅

⋅=

∑

∑

=

=

1

2

2

2

1

α

(M.7)

Where: see above

It is possible to reasonably modify the sample size after the first monitoring event based on the actual variation of the carbon stocks determined from taking the n samples.

2.2.2. Sample plot size

The plot area a has major influence on the sampling intensity and time and resources spent in the field measurements. The area of a plot depends on the stand density. Therefore, increasing the plot area decreases the variability between two samples. According to Freese (1962),26 the relationship between coefficient of variation and plot area can be denoted as follows:

( )212

12

2 / aaCVCV = (M.8)

where a1 and a2 represent different sample plot areas and their corresponding coefficient of variation (CV). Thus, by increasing the sample plot area, variation among plots can be reduced permitting the use of small sample size at the same precision level. Usually, the size of plots is between 100 m2 for dense stands and 1000 m2 for open stands.

2.2.3. Plot location

To avoid subjective choice of plot locations (plot centers, plot reference points, movement of plot centers to more “convenient” positions), the permanent sample plots shall be located systematically with a random start, which is considered good practice in IPCC GPG-LULUCF. This can be accomplished with the help of a GPS in the field. The geographical position, administrative location, stratum and stand, series number of each plots shall be recorded and archived.

Also, it is to be ensured that the sampling plots are as evenly distributed as possible. For example, if one stratum consists of three geographically separated sites, then it is proposed to:

• Divide the total stratum area by the number of plots, resulting in the average area represented by each plot;

• Divide the area of each site by this average area per plot, and assign the integer part of the result to this site. E.g., if the division results in 6.3 plots, then 6 plots are assigned to this site, and 0.3 plots are carried over to the next site, and so on.

26 Freese, F. 1962. Elementary Forest Sampling. USDA Handbook 232. GPO Washington, DC. 91 pp.


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2.2.4. Monitoring frequency

Monitoring interval depends on the variability in carbon stocks and the rate of carbon accumulation, i.e., the growth rate of trees as of living biomass. Although the verification and certification shall be carried out every five years after the first verification until the end of the crediting period (paragraph 32 of decision 19/CP.9), monitoring interval may be less than five years. However, to reduce the monitoring cost, the monitoring intervals shall coincide with verification time, i.e., five years of interval. Logically, one monitoring and verification event will take place close to the end of the first commitment period, e.g. in the second half of the year 2012.

Project participants shall determine the first monitoring time, taking into account:

• The growth rate of trees and the financial needs of the project activity: the later the date of the first verification, the higher will be the amount of net anthropogenic GHG removals by sinks but the lower the financial net present value of a CER;

• Harvesting events and rotation length: The time of monitoring and subsequent verification and certification shall not coincide with peaks in carbon stocks based on paragraph 12 of Appendix B in decision 19/CP.9.

2.2.5. Measuring and estimating carbon stock changes over time

The growth of individual trees on plots shall be measured at each monitoring event. Pre-existing (baseline) trees should conservatively and consistently with the baseline methodology not be measured and accounted for. Although non-tree vegetation such as herbaceous plants, grasses, and shrubs can occur, usually with biomass less than 10 percent, there is also non-tree vegetation on degraded lands and the baseline scenario has assumed the zero stock change for this non-tree biomass. Therefore, non-tree vegetation will not be measured and accounted. The omission of non-tree biomass removals in project scenario makes the monitoring conservative. Even if the initial site preparation results in a removal of non-tree biomass, there is no risk to over-estimate the removals because all pre-existing biomass have been treated as carbon loss during site preparation (see Section III.5.1.1 below). The carbon stock changes in living biomass of trees on each plot are then estimated through Biomass Expansion Factors (BEF) method or allometric equations method.

2.2.6. Monitoring GHG emissions by sources increased as results of the A/R CDM project activity

An A/R CDM project activity may increase GHGs emissions, in particular CO2, CH4 and N2O. The list below contains factors that may result in an increase of GHGs emissions:27

• Emissions of greenhouse gases from burning of fossil fuels for site preparation, logging and other forestry operation;

• Emissions of greenhouse gases from biomass burning for site preparation (slash and burn activity);

• N2O emissions caused by nitrogen fertilization practices.

Changes in GHG emissions caused by these practices can be estimated by monitoring activity data and selecting appropriate emission factors.

27 Refer to Box 4.3.1 and Box 4.3.4 in IPCC GPG-LULUCF.


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3. Calculation of ex post baseline net GHG removals by sinks, if required

Under this methodology there is no need for monitoring the baseline because the per hectare baseline estimates were frozen in the ex ante estimation.

4. Data to be collected and archived for of baseline net GHG removals by sinks

Under this methodology there is no need for monitoring the baseline.

5. Calculation of ex post actual net GHG removal by sinks

The actual net greenhouse gas removals by sinks represent the sum of the verifiable changes in carbon stocks in the carbon pools within the project boundary, minus the increase in GHG emissions measured in CO2 equivalents by the sources that are increased as a result of the implementation of an A/R CDM project activity, while avoiding double counting, within the project boundary, attributable to the A/R CDM project activity. Therefore,28

CACTUAL = ∆CLB + ∆CDW + ∆CLI – Ebiomassloss – GHGE (M.9)

where:






GHGE Sum of the increases in GHG emissions by sources within the project boundary as a result of the implementation of an A/R CDM project activity; t CO2-e

Note: In this methodology Equation M.9 is used to estimate actual net greenhouse gas removals by sinks for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated. The “stock change” method should be used to determine annual or periodical values. The decrease in the carbon stocks of the pre-existing vegetation are initial losses, and therefore accounted once upfront as part of the first monitoring interval, not per year.

28 GPG-LULUCF Equation 3.2.1.


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5.1 Verifiable changes in carbon stocks in the carbon pools

5.1.1. Treatment of pre-existing vegetation and trees

This methodology allows for the simplifying and conservative assumption that all the biomass in tree and non-tree living biomass, deadwood and litter of the pre-project vegetation is removed upon site preparation. Therefore, this methodology includes a carbon-stock decrease on project start, even though in some projects after site preparation pre-project vegetation may remain. At project start, the project can take a discount corresponding to the entire pre-project carbon stocks. Therefore, during the monitoring events, the carbon stocks of remaining pre-project vegetation (e.g., trees left standing) shall be measured and accounted for in the same way as the vegetation that the project establishes.

Ex post, the decrease in the carbon stock in the tree and non-tree living biomass, deadwood and litter carbon pools of pre-existing vegetation due to site preparation shall be estimated in the same way as ex ante. The procedures for the estimation of Ebiomassloss described in Section II.7.1.1 shall be applied here as well.

5.1.2. Estimation of actual ∆CLB (changes in biomass carbon stocks of living trees)

The verifiable carbon stock changes in above-ground biomass and below-ground biomass of living trees within the project boundary are estimated using equation:29

∑∑∑= = =

∆=∆*

1 1 1

t

t

m

i

s

jLBijt

PS PS

CLBC 30 (M.10)

yearCLBCt

t

m

i

s

jLBijt

PS PS

1**

1 1 1∑∑∑

= = =

∆=∆ 31 (M.10)

29 Refers to GPG-LULUCF Equation 3.2.3. 30 In this methodology, time notations and sums over time since project start have been added, while those referring

to “sub-strata” have been deleted. This has been made because “strata” + “sub-strata” are considered “strata” in this methodology (and strata are adjusted ex post - if needed). The sum over time since the start of the project activity is considered necessary as carbon stocks can decrease, and the “sum of changes” over time can better reproduce these ups and downs in carbon stocks (thus showing “net changes”). In addition, the project emissions can only increase and are permanent, which requires accounting for their cumulative value at each point in time.

31 In this methodology, time notations and sums over time since project start have been added, while those referring to “sub-strata” have been deleted. This has been made because “strata” + “sub-strata” are considered “strata” in this methodology (and strata are adjusted ex post - if needed). The sum over time since the start of the project activity is considered necessary as carbon stocks can decrease, and the “sum of changes” over time can better reproduce these ups and downs in carbon stocks (thus showing “net changes”). In addition, the project emissions can only increase and are permanent, which requires accounting for their cumulative value at each point in time.


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where:

∆CLB Sum of the changes in biomass carbon stocks (above- and below-ground) of living trees; t CO2-e

∆CLB ijt Annual carbon stock change in biomass of living trees for stratum i, species j, time t; t CO2-e yr-1

i 1, 2, 3, … mPS ex post strata

j 1, 2, 3, … sPS planted tree species


)( ,, ijtBBijtABLBijt CCC ∆+∆=∆ · MWCO2-C (M.11)

TCCC ijtABijtABijtAB )( 1,2,, −=∆ (M.12)

TCCC ijtBBijtBBijtBB )( 1,2,, −=∆ (M.13)

where:

∆CLB ijt Annual carbon stock change in biomass of living trees Verifiable changes in carbon stock in living biomass of trees for stratum i, species j, time t; t CO2-e yr-1

∆CAB,ijt Changes Annual change in carbon stock in aboveground biomass of living trees for stratum i, species j, time t; t C yr-1

∆CBB,ijt Changes Annual change in carbon stock in belowground biomass of living trees for stratum i, species j, time t; t C yr-1

T Number of years between times t2 and t1 (T = t2-t1); years

CAB,ijt2 Carbon stock in aboveground biomass of living trees for stratum i, species j, calculated at time t=t2; t C

CAB, ijt1 Carbon stock in aboveground biomass of living trees for stratum i, species j, calculated at time t=t1; t C

CBB,ijt2 Carbon stock in belowground biomass of living trees for stratum i, species j, calculated at time t=t2; t C

CBB,ijt1 Carbon stock in belowground biomass of living trees for stratum i, species j, calculated at time t=t1; t C


The mean carbon stocks in above- and below-ground biomass of living trees per unit area are estimated based on field measurements on permanent plots. There are two methods, namely the Biomass Expansion Factors (BEF) method and the Allometric Equations method.


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Method 1: BEF Method

Step 1: Measuring the diameter at breast height (DBH, at 1.3 m above ground) and preferably height of all the trees in the permanent sample plots above a minimum DBH. The minimum DBH varies depending on tree species and climate, for instance, the minimum DBH may be as small as 2.5 cm in arid environments where trees grow slowly, whereas it could be up to 10 cm for humid environments where trees grow rapidly (GPG-LULUCF).

Step 2: Estimating the volume of the commercial component of trees based on locally derived equations, then sum for all trees within a plot and express as volume per unit area (e.g., m3/ha). It is also possible to combine Step 1 and Step 2 if there are field instruments (e.g. relascope) that measure volume of each tree directly.

Step 3: Choosing BEF and root-shoot ratio: The BEF and root-shoot ratio vary with local environmental conditions, species and age of trees, and the volume of the commercial component of trees. These parameters can be determined by either developing a local regression equation or selecting from national inventory, Annex 3A.1 Table 3A.1.10 of GPG LULUCF, or from published sources. If a significant amount of effort is required to develop local BEFs and root-shoot ratio, involving, for instance, harvest of trees, then it is recommended not to use this method but rather to use the resources to develop local allometric equations as described in the allometric method below (refers to Chapter 4.3 in GPG LULUCF). If that is not possible either, national species specific defaults for BEF and R can be used. Since both BEF and the root-shoot ratio are age dependent, it is desirable to use age-dependent equations. Stemwood volume can be very small in young stands and BEF can be very large, while for old stands BEF is usually significantly smaller. Therefore using average BEF value may result in significant errors for both young stands and old stands. It is preferable to use allometric equations, if the equations are available, and as a second best solution, to use age-dependent BEFs (but for very young trees, multiplying a small number for stemwood with a large number for the BEF can result in significant error).

Step 4: Converting the volume of the commercial component of trees into carbon stock in above- and below-ground biomass via basic wood density, BEF, root-shoot ratio and carbon fraction, given by:32

jjjijtijtAB CFBEFDMVMC ⋅⋅⋅=, (M.14)

jijtABijtBB RMCMC ⋅= ,, (M.15)

where:

MCAB, ijt Mean carbon stock in above-ground biomass of living trees per unit area for stratum i, species j, time t; t C ha-1

MCBB, ijt Mean carbon stock in below-ground biomass of living trees per unit area for stratum i, species j, time t; t C ha-1

MVijt Mean merchantable volume per unit area for stratum i, species j, time t; m3 ha-1

32 Refers to GPG LULUCF Equation 4.3.1


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Dj Volume-weighted average wood density for species j; t d.m. m-3 merchantable volume

BEFj Biomass expansion factor for conversion of biomass of merchantable volume to above-ground biomass; dimensionless

CFj Carbon fraction for species j; t C (t d.m)-1 (IPCC default value = 0.5); dimensionless

Rj Root-shoot ratio; dimensionless

Step 5: The total carbon stock in living biomass of trees for each stratum i, species j, time t is calculated from the area of stratum i, species j, time t and the mean carbon stock in above- and below-ground biomass of living trees per unit area, as follows:

CAB, ijt = Aijt · MCAB, ijt (M.16)

CBB, ijt = Aijt · MCBB, ijt (M.17)

where:

CAB, ijt Carbon stock in above-ground biomass of living trees for stratum i, species j, calculated at time t; t C

CBB, ijt Carbon stock in below-ground biomass of living trees for stratum i, species j, calculated at time t; t C

Aijt Area of stratum i, species j, time t; ha

Note: The area of a stratum i planted with species j has a time notation because stands with species j will be established (planted) at different dates.

MCAB, ijt Mean carbon stock in above-ground biomass of living trees per unit area for stratum i, species j, time t; t C ha-1

MCBB, ijt Mean carbon stock in below-ground biomass of living trees per unit area for stratum i, species j, time t; t C ha-1

Step 6: The change in carbon stock in living biomass of trees over time is given by:

∆CAB, ijt = (CAB, ijt2 - CAB, ijt1)/T (M.18)

∆CBB, ijt= (CBB, ijt2 - CBB, ijt1)/T (M.19)

where:

∆CAB, ijt Changes in carbon stock in above-ground biomass of living trees for stratum i, species j, time t; t C yr-1

∆CBB, ijt Changes in carbon stock in below-ground biomass of living trees for stratum i, species j, time t; t C yr-1

CAB, ijt2 Carbon stock in above-ground biomass of living trees for stratum i, species j, calculated at time t=t2; t C


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CAB, ijt1 Carbon stock in above-ground biomass of living trees for stratum i, species j, calculated at time t=t1; t C

CBB, ijt2 Carbon stock in below-ground biomass of living trees for stratum i, species j, calculated at time t=t2; t C

CBB, ijt1 Carbon stock in below-ground biomass of living trees for stratum i, species j, calculated at time t=t1; t C

T Number of years between monitoring time t1 and t2 (T=t2-t1); years

Method 2: Allometric method

Step 1: Measure the diameter at breast height (DBH, at 1.3 m above ground) and preferably height of all the trees in the permanent sample plots above a minimum DBH. The minimum DBH varies depending on tree species and climate, for instance, the minimum DBH may be as small as 2.5 cm in arid environments where trees grow slowly, whereas it could be up to 10 cm for humid environments where trees grow rapidly (IPCC’s GPG-LULUCF). When first measured all trees should be tagged to permit the tracking of individual trees in plots through time. Where a tree has died, been harvested or cannot be found then the biomass at time 2 should be made equal to zero to give the requisite deduction.

Step 2: Choose or establish appropriate allometric equations.

),( HDBHfTB jABj = (M.20)

where:

TBABj Above-ground biomass of a tree of species j; kg tree-1

fj(DBH,H) Allometric equation for species j linking above-ground tree biomass (kg tree-1) to diameter at breast height (DBH) and possibly tree height (H) measured in plots for stratum i, species j, time t; t d.m. ha-1

The allometric equations are preferably local-derived and species-specific. When allometric equations developed from a biome-wide database, such as those in Annex 4A.2, Tables 4.A.1 and 4.A.2 of GPG LULUCF, are used, it is necessary to verify by destructively harvesting, within the project area but outside the sample plots, a few trees of different sizes and estimate their biomass and then compare against a selected equation. If the biomass estimated from the harvested trees is within about ±10% of that predicted by the equation, then it can be assumed that the selected equation is suitable for the project.

Step 3: Estimating carbon stock in above-ground biomass per tree using selected allometric equations applied to the tree measurements in Step 1.

CFTBTC ABAB ⋅= (M.21)

where:

TCAB Carbon stock in above-ground biomass per tree; kg C tree-1

TBAB Above-ground biomass of a tree; kg tree-1

CF Carbon fraction, t C (t d.m)-1, IPCC default value = 0.5

Step 4: Calculate the increment of above-ground biomass carbon accumulation at the tree level. Calculate by subtracting the biomass carbon at time 2 from the biomass carbon at time 1 for each tree.


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∆TCABT = TCAB, t2 – TCAB, t1 (M.22)

where:

∆TCABT Change in above-ground biomass carbon per tree between two monitoring events; kg C tree-1

TCAB, t2 Carbon stock in above-ground biomass per tree, calculated at time t=t2; kg C tree-1

TCAB, t1 Carbon stock in above-ground biomass per tree, calculated at time t=t1; kg C tree-1

Step 5: Calculate the increment in above-ground biomass carbon per plot on a per area basis. Calculate by summing the change in biomass carbon per tree within each plot and multiplying by a plot expansion factor which is proportional to the area of the measurement plot. This is divided by 1,000 to convert from kg to tonnes.

∆PCABT = 1/1000 ∑=

TR

tr 1

∆TCABT, tr XF (M.23)

XF = 1 / AP

where:

∆PCABT Plot level change in above-ground mean carbon stock between two monitoring events; t C ha-1

∆TCABT, tr Change in above-ground biomass carbon per tree tr between two monitoring events; kg C tree-1

XF Plot expansion factor from per plot values to per hectare values


tr Tree (TR = total number of trees in the plot)

Step 6: Calculate mean carbon stock change within each stratum. Calculate by averaging across plots in a stratum or stand:

∆MCABijT = 1 / PLij ∑=

ijPL

pl 1 ∆PCABijT,pl (M.24)

where:

∆MCABijT Mean change in above-ground carbon stock in stratum i, species j, between two monitoring events; t C ha-1.

∆PCABijT,pl Plot-level change in above-ground mean carbon stock in stratum i, species j, between two monitoring events; t C ha-1

PLij Total number of plots in stratum i, species j; dimensionless

pl Plot number in stratum i, species j (PL = total number of plots); dimensionless

Step 7: Estimate carbon stock in below-ground biomass using root-shoot ratios and above-ground carbon stock.

jABBB RTCTC ⋅= (M.25)


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1,2, tBBtBBBB TCTCTC −=∆ (M.26)

∆PCBBT = 1/1000 · ∑=

TR

tr 1

∆TCBBT, tr · XF (M.27)

∆MCBBijT = 1 / PLij · ∑=

ijPL

pl 1∆PCBBijT,pl (M.28)

where:

TCBB Carbon stock in below-ground biomass per tree; kg C tree-1

TCAB Carbon stock in above-ground biomass per tree; kg C tree-1

Rj Root-shoot ratio appropriate to increments for species j; dimensionless

∆PCBBT Plot level change in below-ground mean carbon stock between two monitoring events; t C ha-1

XF Plot expansion factor from per plot values to per hectare values

∆TCBBT, tr Change in below-ground biomass carbon per tree tr between two monitoring events; kg C tree-1

tr Tree (TR = total number of trees in the plot)

∆MCBBijT Mean change in below-ground carbon stock in stratum i, species j, between two monitoring events; t C ha-1

∆PCBBijT,pl Plot level change in below-ground mean carbon stock in stratum i, species j, between two monitoring events; t C ha-1

PLij Total number of plots in stratum i, species j; dimensionless

pl Plot number in stratum i, species j (PL = total number of plots); dimensionless

Step 8: Calculate the change in stock per unit time by dividing by the number of years between monitoring events.

∆MCAB,ijt = ∆MCABijT / T (M.29)

∆MCBB,ijt = ∆MCBBijT / T (M.30)

where:

∆MCAB,ijt Annual mean changes in carbon stock in above-ground biomass for stratum i, species j, at year t; t C ha-1 yr-1

∆MCBB,ijt Annual mean changes in carbon stock in below-ground biomass for stratum i, species j, at year t; t C ha-1 yr-1

∆MCABijT Mean change in above-ground carbon stock in for stratum i, species j, between two monitoring events; t C ha-1 yr-1

∆MCBBijT Mean change in below-ground carbon stock in for stratum i, species j, between two monitoring events; t C ha-1 yr-1

T Number of years between two monitoring events which in this methodology is 5 years; years yr


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Step 9: The annual carbon stock change in living biomass of trees for each stratum i, species j at time t is calculated from the area of each stratum i, species j at time t and the annual mean carbon stock in above- and below-ground biomass per unit area, given by:

ijtABijtijtAB MCAC ,, ∆⋅=∆ (M.31)

ijtBBijtijtBB MCAC ,, ∆⋅=∆ (M.32)

where:

Aijt Area of stratum i, species j, at time t; ha

∆CAB,ijt Changes in carbon stock in above-ground biomass of living trees for stratum i, species j, at time t; t C yr-1

∆CBB,ijt Changes in carbon stock in below-ground biomass of living trees for stratum i, species j, at time t; t C yr-1

∆MCAB,ijt Annual mean change in above-ground carbon stock of living trees in stratum i, species j, at time t; t C ha-1 yr-1

∆MCBB,ijt Annual mean change in below-ground carbon stock of living trees in stratum i, species j, at time t; t C ha-1 yr-1

5.1.3. Estimation of actual ∆CDW (changes in deadwood carbon stocks)

There are two categories of deadwood that may be relevant in the context of the A/R CDM project activity: standing deadwood (DWs) and lying deadwood (DWl). Depending on the specific local circumstances (frequency of thinning and harvesting, extraction or not extraction of thinning and fuel wood volumes) deadwood carbon stocks may accumulate standing and/or lying. Project participants shall decide if they want to account for all sub-pools or for only two or one of them taking into account their project specific circumstances. Monitoring frequency of the deadwood sub-pools may also differ. Since the occurrence of lying deadwood in the early stages of a stand is generally insignificant, lying deadwood may be monitored with a different frequency as that of the tree biomass, while standing deadwood may be monitored with the same frequency.

When monitoring deadwood, care should be taken not to measure deadwood stocks from pre-existing (baseline) trees to be consistent with the baseline methodology. Deadwood density measurements shall be done in accordance with IPCC Good Practice Guidance, Section 4.3.3.5.3.

Changes in deadwood carbon stocks are calculated using the following equation:

∆CDW = ∑∑∑= = =

∆*

1 1 1

t

t

m

i

s

jijtDW

PS PS

C (M.733)

∆CDW = ∑∑∑= =

∆*

1 1 1

1*m

i

s

jijtDW

PS PS

yearC (M.33)


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where:


∆CDWijt Annual carbon stock change in the deadwood carbon pool for stratum i, species j, time t; t CO2-e yr-1




)( ijtDWlijtDWsijtDW CCC ∆+∆=∆ MWCO2-C (M.34)

TCCC ijtDWsijtDWsijtDWs )(12

−=∆ (M.35)

TCCC ijtDWlijtDWlDWlijt)(

12−=∆ (M.36)

where:

∆CDWijt Annual carbon stock change in deadwood for stratum i, species j, time t; t CO2-e yr-1

∆CDWs,ijt Annual carbon stock change in standing deadwood for stratum i, species j, time t; t C yr-1

∆CDWl,ijt Annual carbon stock change in lying deadwood for stratum i, species j, time t; t C yr-1

CDWs,ijt2 Carbon stock in standing deadwood for stratum i, species j, calculated at time t=t2; t C

CDWs,ijt1 Carbon stock in standing deadwood for stratum i, species j, calculated at time t=t1; t C

CDWl,ijt2 Carbon stock in laying deadwood for stratum i, species j, calculated at time t=t2; t C

CDWl,ijt1 Carbon stock in laying deadwood for stratum i, species j, calculated at time t=t1; t C


T Number of years between monitoring time t2 and t1 (T = t2 – t1); years

The total carbon stocks of deadwood for stratum i, species j, time t are calculated from the area for stratum i, species j, time t and the mean carbon stocks in the deadwood sub-pools per unit area, as follows:

CDWs,ijt = Aijt · MCDWs, ijt (M.37)

CDWl,ijt = Aijt · MCDWl, ijt (M.38)

where:

CDWs,ijt Carbon stock in standing deadwood for stratum i, species j, at time t; t C

CDWl,ijt Carbon stock in lying deadwood for stratum i, species j, at time t; t C


MCDWs, ijt Mean carbon stock in standing deadwood per unit area for stratum i, species j, time t; t C ha-1

MCDWl, ijt Mean carbon stock in laying deadwood per unit area for stratum i, species j, time t; t C ha-1


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The mean carbon stocks in standing and lying deadwood per unit area are estimated based on field measurements on permanent plots and transect lines, respectively.

Standing deadwood

Standing dead trees shall be measured using the same criteria and monitoring frequency used for measuring live trees. In addition, the decomposed portion that corresponds to the original living biomass is discounted. The decomposition state of the dead tree and the diameter at breast height shall be recorded and the standing deadwood is categorized under the following four decomposition classes:

(1) Tree with branches and twigs that resembles a live tree (except for leaves);

(2) Tree with no twigs but with persistent small and large branches;

(3) Tree with large branches only;

(4) Bole only, no branches.

The biomass may be estimated as for living trees in decomposition class 1. When only bole is remaining in decomposition classes 2, 3 and 4, it is recommended to estimate the biomass of the main trunk of the tree. If the top of the standing dead tree is missing, the height of the remaining stem is measured and the top diameter is estimated as the ratio of the top diameter to the basal diameter. The volume is converted to carbon as follows:

jdcDWsdcijtDWsdc

ijtijtDWs CFDMVAMC ⋅⋅⋅= ∑ ,, (M.39)

jdcDWsdcijtDWsdc

ijtDWs CFDMVMC **,, ∑= (M.39)

where:

MCDWs, ijt Mean carbon stock in standing deadwood per unit area for stratum i, species j, time t; t C ha-1


MVDWsijj,dc Mean volume in standing deadwood per unit area for stratum i, species j, time t; t C ha-1

DDWsdc Volume-weighted average deadwood density for decomposition class dc; t d.m. m-3 standing deadwood volume

CFj Carbon fraction for species j; t C (t d.m)-1; IPCC default value = 0.5

dc Decomposition class 2, 3, or 4


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Lying deadwood

The lying deadwood can increase as the stand ages. It may be sampled using the line-intersect method as per IPCC GPG (2003). Two 50-meter length lines can be placed at right angles across the each plot centre and the diameters of lying deadwood (≥ 5 cm diameter) intersecting the lines are measured at the intersection. Each deadwood is assigned to one of the three density states ds (sound, intermediate, and rotten), and the volume of lying deadwood in each density state per hectare is calculated using the following equation:33

⋅

++⋅= ∑ LT

DDDMV ijtn

dsdsijtDWl 8

)...( 222

212

, π (M.40)

ds

ijtndsijtDWl LT

DDDMV

⋅++

⋅=8

)...( 222

212

, π (M.40)

jdsDWldsDWlijtds

ijtDWl CFDMVMC **,, ∑= (M.41)

where:

MVDWlijt,ds Mean volume of lying deadwood per area unit in density state ds for stratum i, species j, time t;m3 ha-1

MCDWl, ijt Mean carbon stock in laying deadwood per unit area for stratum i, species j, time t; t C ha-1

D1, D2, …, Dn Diameter of pieces of deadwood in density state ds measured in plots for stratum i, species j, time t; cm

LT Transect length; (100 m)

CFj Carbon fraction for species j; t C (t d.m)-1; IPCC default value = 0.5

dsDWlD Volume-weighted average deadwood density for density state ds; t d.m. m-3 lying deadwood volume

Dsds Deadwood density state (sound, intermediate, and rotten); dimensionless

The mean volumes are converted to carbon using Equation M.39.

5.1.4. Estimation of actual ∆CLI (changes in litter carbon stocks)

Changes in litter carbon stocks are calculated using the following equation:

∆CLI = ∑∑∑= = =

∆*

1 1 1

t

t

m

i

s

jitLI

PS PS

C (M.41)

∆CLI = yearCt

t

m

i

s

jitLI

PS PS

1**

1 1 1∑∑∑

= = =

∆ (M.42)

33 IPCC GPG-LULUCF Equation 4.3.2


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where:


∆CLI it Annual carbon stock change in litter for stratum i, time t; t CO2-e yr-1




∆CLI it = (CLI it 2 – CLI it 1)/T · MWCO2-C (M.43)

where:

CLI it2 Carbon stock in litter for stratum i, calculated at time t=t2; t C

CLI it1 Carbon stock in litter for stratum i, calculated at time t=t1, t C


T Number of years between times t2 and t1 (T = t2-t1); years

The total carbon stocks of litter for stratum i, species j, time t are calculated from the area for stratum i, species j, time t and the mean carbon stocks in the litter sub-pools per unit area, as follows:

CLI it = Ait · MCLI it (M.44)

where:

CLI it Carbon stock in litter for stratum i, at time t; t C

Ait Area of stratum i, at time t; ha

MCLIit Mean carbon stock in litter per unit area for stratum i, time t; t C ha-1

The mean carbon stocks in litter per unit area are estimated based on field measurements. Litter includes all dead biomass of less than 10 cm diameter and dead leaves, twigs, dry grass, and small branches. During early stages of stand development, litter increases rapidly and stabilizes during the later part of the stand. Therefore, if seasonal effects apply to the project region, litter samples shall be collected at the same time of the year in order to account for natural and anthropogenic influences on the litter accumulation and to eliminate seasonal effects.

Step 1: Litter shall be sampled using a 30 cm radius circular frame. The frame is placed four times at random locations or plot corners within the small nested plot (10 m x 5 m).

Step 2: At each location, all litter (leaves, fruits, small wood, etc.) within the frame shall be collected.

Step 3: The collected litter is oven dried and weighed to determine the dry weight and analysed in the laboratory to estimate the carbon content. If laboratory method is not feasible, the dry mass of litter shall be converted into carbon using the default carbon fraction (0.370) used for litter as recommended by the GPG/LULUCF (Chapter 3.2, p.3.36).

MCLI it = MWLI it · CFLI it (M.45)


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where:

MCLI it Mean carbon stock in litter per unit area for stratum i, time t; t C ha-1

MWLI it Mean weight of litter per unit area for stratum i, time t; t d.m. ha-1

CFLI it Carbon fraction of litter from stratum i, time t as determined in laboratory analysis if feasible (default value = 0.370); t C (t d.m)-1

5.2. GHG emissions by sources

The increase in GHG emission as a result of the implementation of the proposed A/R CDM project activity within the project boundary can be estimated by:

+= tFuelBurntE EGHG ,, tfertilizerNdirecttnBiomassBurCONon ONE,2 2,, −− + (M.46)

where:

GHGE,t Increase in GHG emission as a result of the implementation of the proposed A/R CDM project activity within the project boundary in year t; t CO2-e yr-1

EFuelBurn,t Increase in GHG emission as a result of burning of fossil fuels within the project boundary in year t; t CO2-e yr-1

ENon-CO2,BiomassBurn,t Increase in non-CO2 emission as a result of biomass burning within the project boundary in year t; t CO2-e yr-1

N2Odirect-Nfertilizer, t Increase in N2O emission as a result of direct nitrogen application within the project boundary in year t; t CO2-e yr-1

Note: In this methodology Equation M.45 is used to estimate the increase in GHG emission for the period of time elapsed between project start (t = 1) and the year t = t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated.

5.2.1. GHG emissions from burning of fossil fuel

In the context of the afforestation or reforestation, the increase in GHG emission by burning of fossil fuels is most likely resulted from machinery use during site preparation, thinning and logging.

Step 1: Monitoring the type and amount of fossil fuels consumed in site preparation and/or logging. This can be done using indirect methods (e.g. Hours of machine use x average fuel consumption per hour; traveled kilometers x average fuel consumption per traveled kilometer; cubic meters harvested x average fuel consumption per cubic meter, etc).

Step 2: Choosing emission factors. There are three possible sources of emission factors:

• National emission factors: These emission factors may be developed by national programs such as national GHG inventory;

• Regional emission factors;



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Step 3: Estimating of GHG emissions resulted from the burning of fossil fuel during site preparation and logging. Although some non-CO2 GHG (CO, CH4, NMVOCs) may be released during combustion process, all the released carbon are accounted as CO2 emissions based on the 2006 IPCC Guidelines for energy:

001.0)( ,,, ⋅⋅+⋅= gasolinetgasolinedieseltdieseltFuelBurn EFCSPEFCSPE (M.46)

∑=

∗∗+∗=*

1,, 001.0)(

t

tgasolinetgasolinedieseltdieselFuelBurn EFCSPEFCSPE (M.47)

where:

EFuelBurn,t Increase in GHG emission as a result of burning of fossil fuels within the project boundary for the period of time elapsed between project start (t = 1) and the year t = t*in year t; t CO2-e yr-1

CSPdiesel,t Amount of diesel consumption in year t; liter (l) yr-1

CSPgasoline,t Amount of gasoline consumption in year t; liter (l) yr-1

EFdiesel Emission factor for diesel; kg CO2 l-1

EFgasoline Emission factor for gasoline; kg CO2 l-1


5.2.2. GHG emissions from biomass burning

Slash and burn or removal of pre-existing vegetation occurs traditionally in some regions during site preparation before planting and/or replanting. Since this methodology covers CO2 emission as a verifiable change in the carbon stocks of the carbon pools, only non-CO2 emissions are accounted here.

Step 1: Estimating the mean above-ground biomass stock per unit area before slash and burn. Usually, herbaceous plants and shrubs dominate pasture or agricultural land, degraded land or logged land. Therefore, this value can be obtained by following simple harvesting techniques:

The herbaceous plants can be measured by simple harvesting techniques. A small frame (either circular or square), usually encompassing about 0.5-1.0 m2 or less, is used to aid this task. The material inside the frame is cut to ground level and weighed, and the underground part is also dug and weighed. Well-mixed samples are then collected and oven dried to determine dry-to-wet matter ratios. These ratios are then used to convert the entire sample to oven-dry matter. For shrubs, destructive harvesting techniques can also be used to measure the living biomass. An alternative approach, if the shrubs are large, is to develop local shrub allometric equations based on variables such as crown area and height or diameter at base of plant or some other relevant variable (e.g., number of stems in multi-stemmed shrubs). The equations would then be based on regressions of biomass of the shrub versus some logical combination of the independent variables. The independent variable or variables would then be measured in the sampling plots (Refers to Chapter 4.3 in GPG LULUCF).

If average carbon stocks for agricultural land uses are to be determined, peak carbon stocks in the management cycle shall be used.


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Step 2: Estimating combustion efficiencies and emission factors. The combustion efficiencies may be chosen from Table 3.A.14 of GPG-LULUCF. If no appropriate combustion efficiency can be used, the IPCC default of 0.5 should be used. The nitrogen-carbon ratio (N/C ratio) is approximated to be about 0.01. This is a general default value that applies to leaf litter, but lower values would be appropriate for fuels with greater woody content, if data are available. Emission factors for use with above equations are provided in Tables 3.A 15 and 3.A.16 of GPG-LULUCF.

Step 3: Estimating of GHG emissions resulted from the slash and burn based on 2006 IPCC Guidelines for LULUCF and GPG LULUCF:

1422 ,,,, =∀+=− tEEE CHnBiomassBurONnBiomassBurtnBiomassBurCONon (M.47)

142 ,,, =∀=− tEE CHnBiomassBurtnBiomassBurCONon (M.48)

ENon-CO2,BiomassBurn, t = 0 >∀ t 1 (M.49)

where:

ENon-CO2,BiomassBurn,t The increase in non-CO2 emission as a result of biomass burning in slash and burn at start of the project; t CO2-e yr-1



EBiomassBurn, N2O = EBiomassBurn,C · (N/C ratio) · ERatN2O · MWN2O-N · GWPN2O (M.49)

EBiomassBurn, CH4 = EBiomassBurn,C · ERatCH4 · MWCH4-C · GWPCH4 (M.50)

where:34



EBiomassBurn,C Loss of above-ground biomass carbon due to slash and burn; t C yr-1

N/C ratio Nitrogen-carbon ratio; t N (t C)-1


MWCH4-C Ratio of molecular weights of CH4 and C (16/12); t CH4 (t C)-1

ERatN2O IPCC default emission ratio for N2O (0.007); dimensionless

ERatCH4 IPCC default emission ratio for CH4 (0.012); dimensionless


GWPCH4 Global Warming Potential for CH4 (21 for the first commitment period); t CO2-e (t CH4)-1

34 Refers to Table 5.7 in 1996 Revised IPCC Guideline for LULUCF and Equation 3.2.19 in GPG LULUCF.


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∑ ⋅⋅⋅=PSm

iiiburnCnBiomassBur CFCEBAE ,, (M.51)

where:

EBiomassBurn,C Loss of above-ground biomass carbon due to slash and burn; t C yr-1

Aburn,i Area of slash and burn for stratum i; ha yr-1

Bi Average above-ground stock in living biomass before burning for stratum i; t d.m. ha-1

CE Combustion efficiency (IPCC default =0.5); dimensionless

CF Carbon fraction of dry biomass; t C (t d.m)-1

i Stratum (mPS = total number of strata)

5.2.3. Nitrous oxide emissions from nitrogen fertilization practices

Only direct N2O emissions from nitrogen fertilization are monitored and estimated in this methodology, because indirect N2O emissions (e.g., leaching and runoff) are smaller in forest than in agricultural land and the emission factor used in the 2006 IPCC Guidelines appears to be high (GPG LULUCF). The method of 2006 IPCC Guidelines, GPG-2000 and GPG LULUCF can be used to estimate the direct N2O emissions.

Step 1: Monitoring and estimating the amount of nitrogen in synthetic and organic fertilizer used within the project boundary:35

NSN-Fert = ∑∑∑===

PSPS s

j

m

i

t

t 11

*

1

Aijt · NSN-Fert ijt · 0.001 (M.52)

NSN-Fert = ∑∑∑===

PSPS s

j

m

i

t

t 11

*

1

Aijt · NSN-Fert ijt *1 year* 0.001 (M.52)

NON-Fert = ∑∑∑===

PSPS s

j

m

i

t

t 11

*

1

Aijt · NON-Fert ijt · 0.001 (M.53)

NON-Fert = ∑∑∑===

PSPS s

j

m

i

t

t 11

*

1

Aijt · NON-Fert ijt *1 year* 0.001 (M.53)

35 Refers to Equation 3.2.18 in IPCC GPG-LULUCF.


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where:

NSN-Fert Total amount of synthetic fertilizer within the project boundary ; t N

Note: This quantity could also be estimated by monitoring and recording annual purchases and use of synthetic fertilizers at the project level (instead of the actual consumption at the stand level, Aijt )

NSN-Fert Total amount of synthetic fertilizer within the project boundary; t N

Note: This quantity could also be estimated by monitoring and recording annual purchases and use of synthetic fertilizers at the project level (instead of the actual consumption at the stand level, Aijt )

NON-Fert Total amount of organic fertilizer within the project boundary; t N

Note: This quantity could also be estimated by monitoring and recording annual purchases and use of synthetic fertilizers at the project level (instead of the actual consumption at the stand level, Aijt)

NSN-Fert ijt Use of synthetic fertilizer per unit area for stratum i, tree species i in year t; kg N ha-1 yr-1

NON-Fert,ijt Use of organic fertilizer per unit area for stratum i, tree species i in year t; kg N ha-1 yr-1




Step 2: Choosing the fractions of synthetic and organic fertilizer nitrogen that is emitted as NOX and NH3, and emission factors. As noted in GPG 2000 and 2006 IPCC Guidelines, the default emission factor is 1.25 % of applied N, and this value should be used when country-specific factors are unavailable. Project developer may develop specific emission factors that are more appropriate for their project. Specific good practice guidance on how to derive specific emission factors is given in Box 4.1 of GPG 2000. The default values for the fractions of synthetic and organic fertilizer nitrogen that are emitted as NOX and NH3 are 0.1 and 0.2 respectively in 2006 IPCC Guidelines:36

Step 3: Calculating direct N2O emissions from nitrogen fertilization.37

1,2 )( EFFFON ONSNtNdirect fertilizer⋅+=− · MWN2O-N · GWPN2O (M.54)

)1(, GASFtFertSNSN FracNF −⋅= − (M.55)

)1(, GASMtFertONON FracNF −⋅= − (M.56)

12 )( EFFFON ONSNNdirect fertilizer⋅+=− · MWN2O-N · GWPN2O (M.54)

)1( GASFFertSNSN FracNF −⋅= − (M.55)

)1( GASMFertONON FracNF −⋅= − (M.56)

36 Refers to Table 4-17 and Table 4-18 in 1996 IPCC Guidelines. 37 Refers to Equation 3.2.18 in IPCC GPG-LULUCF, Equation 4.22 and Equation 4.23 in GPG 2000.


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where:

N2Odirect-Nfertilizer Total direct N2O emission as a result of nitrogen application within the project boundary at time t*; t CO2-e

FSN Total amount of synthetic fertilizer nitrogen applied adjusted for volatilization as NH3 and NOX; t N

FON Total amount of organic fertilizer nitrogen applied adjusted for volatilization as NH3 and NOX; t N

NSN-Fert Total amount of synthetic fertilizer applied within the project boundary Amount of synthetic fertilizer nitrogen applied; t N yr-1

NOSN-Fert Total amount of organic fertilizer applied within the project boundary Amount of organic fertilizer nitrogen applied; t N yr-1

EF1 Emission factor for emissions from N inputs; t N2O-N (t N input)-1

FracGASF Fraction that volatilises as NH3 and NOX for synthetic fertilizers; t NH3-N and NOX-N (t N)-1

FracGASMF Fraction that volatilises as NH3 and NOX for organic fertilizers; t NH3-N and NOX-N (t N)-1




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6. Data to be collected and archived for actual net GHG removals by sinks

ID number Data Variable Data unit Data source

Measured (m) calculated (c) estimated (e)

Recording frequency

Proportion of data monitored Comment

2.1.1.01 Stratum ID Alpha numeric Stratification map, GIS

Before and after the start of the project

100% Each stratum has a particular combination of soil type, climate, and possibly tree species

2.1.1.02 Stand ID Alpha numeric Stand map, GIS At stand establishment

100% Each stand has a particular year to be planted under each stratum

2.1.1.03 Confidence level % Before the start of the project

100% For the purpose of QA/QC and measuring and monitoring precision control

2.1.1.04 Precision level % Before the start of the project

100% For the purpose of QA/QC and measuring and monitoring precision control

2.1.1.05 Standard deviation of each stratum

e At each monitoring event

100% Used for estimating numbers of sample plots of each stratum and stand, as necessary

2.1.1.06 Number of sample plots c Before the start of the project and adjusted thereafter

100% For each stratum calculated from 2.1.1.03-2.1.1.05

2.1.1.07 Sample plot ID Alpha numeric Project and plot map, GIS

Before the start of the project

100% Numeric series ID will be assigned to each permanent sample plot

2.1.1.08 Plot location Project and plot map and GPS locating, GIS

m 5 years 100% Using GPS to locate before start of the project and at time of each field measurement

2.1.1.09 Tree species Project design map 5 years 100% Arranged in PDD 2.1.1.10 Age of plantation Year GIS m At stand

establishment 100% Counted since the planted year

2.1.1.11 Number of trees Number Plot measurement m 5 years 100% trees in plots

Counted in plot measurement


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Recording frequency


2.1.1.12 Diameter at breast height of living and standing dead trees (DBH)

cm (living/dead) Plot measurement m 5 year 100% trees in plots

Measuring at each monitoring time per sampling method

2.1.1.13 Mean DBH cm Calculated c 5 year 100% of sampling plots

Calculated from 2.1.1.11 and 2.1.1.12

2.1.1.14 Height of living and dead trees

m Plot measurement m 5 year 100% trees in plots


2.1.1.15 Mean tree height m Calculated c 5 year 100% of sampling plots

Calculated from 2.1.1.11 and 2.1.1.14

2.1.1.16 Merchantable volume m3.ha-1 Calculated or plot measurement

c/m 5 year 100% of sampling plots

Calculated from 2.1.1.13 and possibly 2.1.1.15 using local-derived equations, or directly measured by field instrument

2.1.1.17 Wood density t d.m. m-3 Local-derived, national inventory, GPG for LULUCF

e 5 year 100% of sampling plots

Local-derived and species-specific value have the priority

2.1.1.18 Biomass expansion factor (BEF)

Dimensionless Local-derived, national inventory, GPG for LULUCF



2.1.1.19 Carbon fraction t C.(t d.m)-1 Local, national, IPCC



2.1.1.20 Root-shoot ratio Dimensionless Local-derived, national inventory, GPG for LULUCF



2.1.1.21 Carbon stock in above-ground biomass of stands

t C Calculated from equation

c 5 year 100% of strata Calculated from 2.1.1.23 and 2.1.1.25

2.1.1.22 Carbon stock in below-ground biomass of stands

t C Calculated from equation

c 5 year 100% of strata Calculated from 2.1.1.24 and 2.1.1.25

2.1.1.23 Mean Carbon stock in above-ground biomass per unit area per stratum per species

t C ha-1 Calculated from plot data

c 5 year 100% of stands Calculated from 2.1.1.6 -2.1.1.19 or 2.1.1.24 and 2.1.1.25


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Recording frequency


2.1.1.24 Mean carbon stock in below-ground biomass per unit area per stratum per species

t C ha-1 Calculated from plot data

c 5 year 100% of stands Calculated from 2.1.1.23 2.1.1.06 and 2.1.1.20

2.1.1.25 Area of stand ha Stratification map and stand data, GIS

m At stand establishment

100% of stands Actual area of each stand

2.1.1.26 Deadwood category of standing tree

Dimensionless Plot measurement m 5 year 100% of sampling plots


2.1.1.27 Diameter of lying dead tree in each density class

cm/density class Plot measurement m 5 year or more 100% of strata and stands


2.1.1.28 Carbon stock change in above-ground biomass

t C yr-1 Calculated from equation

c 5 year 100% of strata Calculated from 2.1.1.21

2.1.1.29 Carbon stock change in below-ground biomass

t C yr-1 Calculated from equation

c 5 year 100% of strata Calculated from 2.1.1.22

2.1.1.30 Deadwood stock t C Calculated from equations

c 5 year 100% of strata Calculated from 2.1.1.25- 2.1.127and 2.1.1.17-2.1.1.20

2.1.1.31 Decomposition rate % yr-1 Plot measurement m 5 year Experimental plots

Field measurements

2.1.1.32 Carbon stock change in deadwood

t C Calculated from equations

c 5 year 100% of strata Calculated

2.1.1.33 Annually harvested volume and fuel wood

m3 Harvesting statistics c Annually 100% stands Annually recorded

2.1.1.34 Annual carbon stock change in litter

t C yr-1 Calculated from formula

c 5 year 100% of strata and stands

Calculated from 2.1.1.35

2.1.1.35 Mean carbon stock in litter

t C Calculated from formula

c 5 year 100% of strata and stands

Calculated from 2.1.1.35

2.1.1.36 Mean weight of litter t ha-1 Laboratory measurement

m 5 year 100% of strata and stands

Measuring at each monitoring time

2.1.1.37 Carbon fraction of litter t C (t d.m.)-1 Laboratory measurement

m 5 year 100% of strata and stands

Measuring at each monitoring time


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Recording frequency


2.1.2.01 Amount of diesel consumed in machinery use for site prep, thinning or logging

On-site monitoring Liter m Annually 100% Measuring either diesel consumption per unit area for site preparation, or per unit volume logged or thinned

2.1.2.02 Amount of gasoline consumed in machinery use for site prep, thinning or logging

On-site monitoring Liter m Annually 100% Measuring either diesel consumption per unit area for site preparation, or per unit volume logged or thinned

2.1.2.03 Emission factor for diesel GPG 2000, IPCC Guidelines, national

inventory

kg/ liter e At beginning of the project

100% National inventory value should has priority

2.1.2.04 Emission factor for gasoline

GPG 2000, IPPCC Guidelines, national

inventory

kg/ liter e At beginning of the project

100% National inventory value should has priority

2.1.2.05 Emission from fossil fuel use within project boundary

Calculated from Equation (23)

t CO2-e yr-1 e Annually 100% Calculating using Equation (23) via 2.1.2.01-2.1.2.04

2.1.2.06 Area of slash and burn Measured during implementation

ha m During the first year of the project duration

100% Measured for different strata and sub-strata

2.1.2.07 Mean biomass stock per unit area before slash and burn

Measured before slash and burn

t d.m. ha-1 m During the first year of the project duration

100% Sampling survey for different strata and sub-strata before slash and burn

2.1.2.08 Proportion of biomass burnt

Measured after slashand burn

Dimensionless m During the first year of the project duration

100% Sampling survey after slash and burn

2.1.2.09 Biomass combustion efficiency

GPG LU-LUCF National inventory

Dimensionless e Before the start of the project

100% IPCC default value (0.5) is used

2.1.2.10 Carbon fraction Local, national, IPCC

t C.(t d.m)-1 e Before the start of the project

100% 2.1.1.19 can be used if no appropriate value

2.1.2.11 Loss of above-ground biomass carbon due to slash and burn

Calculated using Equation

t C yr-1 c During the first year of the project duration

100% Calculated using Equation


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Recording frequency


2.1.2.12 N/C ratio GPG LU-LUCF National inventory,

publications

t N (t C)-1 e Before the start of the project

100% IPCC default value (0.01) is used if no appropriate value

2.1.2.13 N2O emission from biomass burn


t CO2-e yr-1 c During the first year of the project duration

100% Calculated using Equation via 2.1.2.11-2.1.2.12

2.1.2.14 CH4 emission from biomass burn


t CO2-e yr-1 c During the first year of the project duration

100% Calculated using Equation via 2.1.2.11

2.1.2.16 Amount of synthetic fertilizer N applied per unit area

Monitoring activity kg N ha-1 yr-1 m Annually 100% For different tree species and/or management intensity

2.1.2.17 Amount of organic fertilizer N applied per unit area

Monitoring activity kg N ha-1 yr-1 m Annually 100% For different tree species and/or management intensity

2.1.2.18 Area of land with N applied

Monitoring activity ha yr-1 m Annually 100% For different tree species and/or management intensity

2.1.2.19 Amount of synthetic fertilizer N applied


t N yr-1 c Annually 100% Calculated using Equation via 2.1.2.16 and 2.1.2.18

2.1.2.20 Amount of organic fertilizer N applied


t N yr-1 c Annually 100% Calculated using Equation via 2.1.2.17 and 2.1.2.18

2.1.2.21 Fraction that volatilises as NH3 and NOX for synthetic fertilizers

GPG 2000, GPG LU-LUCF, IPCC

Guideline National inventory

t NH3-N and NOX-N (t N)-1

e Before start of monitoring

100% IPCC default value (0.1) is used if no more appropriate data

2.1.2.22 Fraction that volatilises as NH3 and NOX for organic fertilizers


Guidelines National inventory

t NH3-N and NOX-N (t N)-1

e Before start of monitoring

100% IPCC default value (0.2) is used if no more appropriate data

2.1.2.23 Emission factor for emission from N input


Guidelines National inventory

N2O N-input-1 e Before start of monitoring

100% IPCC default value (1.25%) is used if no more appropriate data


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Recording frequency


2.1.2.24 Direct N2O emission of N input


t CO2-e yr-1 c Annually 100% Calculated using Equation via 2.1.2.19-2.1.2.23


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7. Leakage

Leakage represents the increase in GHG emissions by sources, which occurs outside the boundary of an A/R CDM project activity that is measurable and attributable to the A/R CDM project activity.

This methodology applies to A/R CDM project activities that have four likely sources of leakage:

• GHG emissions caused by vehicle fossil fuel combustion due to transportation of seedling, labour, staff and harvest products to and/or from project sites;

• GHG emissions caused by displacement of people. These people have no influence over pre-project land use, and therefore do not fall under the activity displacement leakage (e.g., these people could be employees).

• Carbon stock decreases caused by displacement of pre-project grazing;

• Carbon-stock decreases caused by the displacement of fuel-wood collection;

• Carbon-stock decreases due to the increased use of wood posts for fencing.

LK = LKVehicle + LKPeopleDiscplacement + LKConversion + LK fuel-wood + LK fencing (M.57)

where:

LK Total leakage; t CO2-e

LKPeopleDisplacement Total leakage due to deforestation due to people displacement; t CO2-e

LKConversion Leakage due to conversion of land to grazing land; t CO2-e

LKVehicle Total GHG emissions due to fossil fuel combustion from vehicles; t CO2-e

LK fuel-wood Leakage due to the displacement of fuel-wood collection; t CO2-e


Note: In this methodology Equation M.57 is used to estimate leakage for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated.

In line with the applicability conditions 13, this methodology excludes the following source of leakage:

• GHG emissions and carbon-stock decreases outside the project boundary caused by displacement of pre-project grazing activities.

7.1. Estimation of LKVehicle (leakage due to fossil fuel consumption)

Leakage due to fossil fuel combustion from vehicles shall be estimated using the A/R Methodological Tool for “Estimation of GHG emissions related to fossil fuel combustion in A/R CDM project activities” where that is: following steps and formulae.

∑=

=*

1,

t

yyFCVehicle ETLK (M.58)


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where:

LKVehicle Total GHG emissions due to fossil fuel combustion from vehicles; t CO2-e



Step 1: Collecting the traveled distance of different types of vehicles using different fuel types.

Step 2: Determining emission factors for different types of vehicles using different fuel types. Country-specific emission factors shall be developed and used if possible. Default emission factors provided in the IPCC Guidelines and updated in the GPG 2000 may be used if there are no locally available data.

Step 3: Estimating the GHG emissions using bottom-up approach described in GPG 2000 for energy sector38.

2,COVehicleVehicle LKLK = (M.59)

∑∑∑=

⋅=*

1, )(

2

t

txyt

x yxyCOVehicle mptionFuelConsuEFLK (M.60)

xytxytxytxyt eknptionFuelConsum ⋅⋅= (M.61)

where:

LKVehicle Total GHG emissions due to fossil fuel combustion from vehicles; t CO2-e yr-1

LKVehicle,CO2 Total CO2 emissions due to fossil fuel combustion from vehicles; t CO2-e yr-1

x Vehicle type

y Fuel type


FuelConsumptionxyt Consumption of fuel type y of vehicle type x at time t; liters


kxyt kilometers traveled by each of vehicle type x with fuel type y at time t; km



Country-specific emission factors shall be used if available. Default emission factors provided in the IPCC Guidelines and updated in the GPG 2000 may be used if there are no locally available data.

7.2. Estimation of LKPeopleDisplacement (leakage caused by displacement of people that have no influence over pre-project land use, and therefore do not fall under the activity displacement leakage)

38 Refer to Equation 2.5 and Equation 2.6 in IPCC GPG 2000 for energy sector.


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By terminating a current land use, the A/R CDM activity may cause the loss of employment, and therefore cause the displacement of former employees. These people do not have influence over pre-project land use, and therefore do not fall under the activity displacement leakage. People displacement leakage may occur in the years immediately after employees are made redundant, when these individuals displaced by the project establish their new livelihoods. This leakage does not necessarily occur immediately after the start of the project activity, since the project’s planting activities may provide initial employment.

If employment is lost, some of the displaced employees and their households may decide to establish a farm as their new livelihood. Establishment of new farms may lead to deforestation. Where forest loss occurs through the actions of the displaced households a leakage debit will be taken by the project, which will be determined as follows:

Step 1: Prior to the start of project activities, record the number of employees that the pre-project land uses sustain. Randomly select at least 10% of the employees that may be displaced by the project.

Step 2: Return at least 1 year but at most 5 years after the project start to determine how many permanent jobs were lost. Among the employees randomly selected in Step 1, record the households that have moved and cannot be monitored further. For households that cannot be monitored, follow Steps 4 and 5 below. For households that can be monitored record the area deforested by them.

Step 3: Return at least 1 year but at most 5 years after the conclusion of the project’s initial planting activities to determine how many permanent jobs were lost. Record the households that have moved and cannot be monitored further. For households that cannot be monitored, follow Step 4 below. For households that can be monitored record the area deforested by them.

Step 4: Where a sampled household has moved away and can not be monitored further, there is some possibility that the household has established a new farm for its livelihood and caused deforestation. Project proponents shall present transparent and verifiable information regarding the average area of smallholder farms in the region.

Project proponents shall estimate the likelihood that a household that has moved has established a new farm based on an analysis of trends for rural-rural and rural-urban migration in the region or the country. Sources for estimating migration trends include official data (e.g., regional or national demographic censuses) and expert opinions. In order to be conservative, all displacement of workers is assumed to lead to a move and all rural-rural migration is assumed to lead to colonization (i.e. new farm establishment and not new wage employment elsewhere). (For instance, the project proponents shall assume that 3 households established a new farm, if 5 households cannot be found and if national census reports indicate that 60% of internal migration originating from rural areas involves moves to other rural areas, rather than moves to cities.)

Step 5: Sum the leakage for all sampled households. As at least 10% of households were sampled, calculate the total leakage of all households from the summed leakage of all sampled households.

LKPeopleDisplacement = ∑=

H

hhAD

1

· FS · 100 / 10 (M.62)


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where:

LKPeopleDiscplacement Total leakage due to deforestation due to people displacement; t CO2-e

ADh Area deforested by displaced household h; ha

Note: the area can be either recorded or estimated

FS Mean carbon stock of primary forests according to the GPG-LULUCF, Table 3A 1.4, pages 3.159-3.162; t CO2-e ha-1

h 1, 2, 3, ..., H, individual employments lost

Note: The factor of 10 may have to be adjusted, if a larger fraction than 10% of the households were sampled.

Any later displacement of former employees of the pre-project land-uses on the project sites will not be attributed to the project.

7.2. Estimation of LKConversion (Leakage due to conversion of land to grazing land) Demonstrate that leakage from activity displacement due to displacement of pre-project grazing activities does not occur

Leakage due to conversion of land to grazing land (LKConversion) shall be monitored and calculated using the latest version of the A/R methodological tool: “Estimation of GHG emissions related to displacement of grazing activities in A/R CDM project activity” that is:

∑=

=*

1,

t

ttntDisplacemeConversion LKLK (M.59)

where:

LKConversion Leakage due to conversion of land to grazing land; t CO2-e

LKDisplacement,t Leakage due to the displacement of animals in year t; t CO2-e


Following applicability condition 13, this methodology is only applicable if the project proponents can demonstrate that the cattle are not displaced somewhere else, but slaughtered or sold to be slaughtered. The project proponents shall provide evidence of what happened to the cattle at the initial verification.

7.3. Estimation of LK fuel-wood (Leakage due to displacement of fuel-wood collection)

Step 1: For each verification period, estimate the average fuel-wood collection in the project area to estimate the volume of fuel-wood gathering displaced outside the project boundary. Monitoring can be done by periodically interviewing households, through a Participatory Rural Appraisal (PRA) or field-sampling.

tARBLtoutside FGFGFG ,, −= (M.60)


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where:


FGBL Average pre-project annual volume of fuel-wood gathering in the project area – estimated ex ante and specified in the CDM-AR-PDD; m3 yr-1

FGAR,t Volume of fuel-wood gathered in the project area according to monitoring results; m3 yr-1

Step 2: Leakage due to displacement of fuel-wood collection can be set as zero (LK fuel-wood = 0) under the following circumstances:

• FGBL < FGAR,t;

• LK fuel-wood < 2% of actual net GHG removals by sinks (See EB 22, Annex 15).

If one of the above assumptions was made in the CDM-AR-PDD, it is necessary to monitor FGArt and/or FGNGLt to prove that the assumption is still valid.

In all other cases, leakage due to displacement of fuel-wood collection shall be estimated as follow (IPCC GPG-LULUCF – Equation 3.2.8):

LKfuel-wood = ∑=

*

1

t

t

FGt · D · R · CF · MWCO2-C (M.65)

LKfuel-wood = ∑=

*

1

t

t

FGt · D · R · CF · MWCO2-C *1 year (M.61)

FGt = FGoutside,t (M.62)

where:


FGt Volume of fuel-wood gathering displaced in unidentified areas; m3 yr-1

FGoutside,t Volume of fuel-wood gathering displaced outside the project area at year t – as per Step 1; m3 yr-1

D Average basic wood density; t d.m. m-3 (See IPCC GPG-LULUCF – Table 3A.1.9)

CF Carbon fraction of dry matter (default = 0.5); t C (t d.m.)-1

R Root-shoot ratio; dimensionless



7.4. Estimation of LKfencing (Leakage due to increased use of wood posts for fencing)

Step 1: Monitor the lengths of the perimeters that are fenced (PARt), average distance between wood posts (DBP) and the fraction of posts that is produced off-site from non-renewable sources (FNRP).


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Step 2: Estimate leakage due to increased use of wood posts for fencing as follow:

∑=

⋅=*

1

t

t

tfencing FNRP

DBPPARLK ⋅⋅⋅⋅⋅ CFBEFDAPV 2 MWCO2-C (M.63)

where:

LKfencing Leakage due to increased use of wood posts for fencing up to year t*; t CO2

PARt Perimeter of the areas to be fenced at year t; m

DBP Average distance between wood posts; m

FNRP Fraction of posts from off-site non-renewable sources; dimensionless

APV Average volume of wood posts (estimated from sampling); m3

D Average basic wood density of the posts; t d.m. m-3 (See IPCC GPG-LULUCF – Table 3A.1.9)

BEF2 Biomass expansion factor for converting volumes of extracted round-wood to total above-ground biomass (including bark); dimensionless Table 3A.1.10

CF Carbon fraction of dry matter (default = 0.5); t C (t d.m.)-1

MWCO2-C Ratio of molecular weights of CO2 and C (44/12); CO2 (t C)-1


Note: As per the guidance provided by the Executive Board (See EB 22, Annex 15) leakage due to increased use of wood posts for fencing can be excluded from the calculation of leakages if LKfencing < 2% of actual net GHG removals by sinks (See EB 22, Annex 15).


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8. Data to be collected and archived for leakage


Measured (m) Calculated (c) estimated (e)

Recording frequency

Proportion of data

monitored Comment

3.1.01 Number of each vehicle type used

Number Monitoring of project activity

m Annually 100% Monitoring number of each vehicle type used

3.1.02 Emission factors for road transportation

kg CO2-e l-1 GPG 2000, IPCC Guidelines, national inventory

e Annually 100% National or local value has the priority

3.1.03 Kilometers travelled by vehicles km Monitoring of project activity

m Annually 100% Monitoring km for each vehicle and fuel type

3.1.04 Fuel consumption per km l km-1 Local data, national data, IPCC

e 5 years 100% Estimated for each vehicle and fuel type

3.1.05 Fuel consumption for road transportation

l Calculated via 3.1.01, 3.1.03, 3.1.04

c Annually 100% Calculated via 3.1.01, 3.1.03, 3.1.04

3.1.06 Leakage due to vehicle use for transportation

t CO2-e yr-1 Calculated via 3.1.02, 3.1.05

c Annually 100% Calculated via 3.1.02, 3.1.05

3.1.07 Leakage due to conversion of land to grazing land

t CO2-e yr-1 Calculated using A/R methodological tool “Estimation of GHG emissions related to displacement of grazing activities in A/R CDM project activity”

c Annually 100% Calculated using A/R methodological tool “Estimation of GHG emissions related to displacement of grazing activities in A/R CDM project activity”

3.1.17 Average pre-project annual volume of fuel-wood gathering in the project area

m3 yr-1 Interview e Prior to the start of project

activities

3.1.18 Volume of fuel-wood gathered in the project area

m3 yr-1 Interview e During monitoring

3.1.19 Leakage due to displacement of fuel-wood collection up to year t*

t CO2-e Calculated c During monitoring


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Measured (m) Calculated (c) estimated (e)

Recording frequency

Proportion of data

monitored Comment

3.1.20 Volume of fuel-wood gathering displaced in unidentified areas

m3 yr-1 Interviews c During monitoring

3.1.21 Volume of fuel-wood gathering displaced outside the project area at year t

m3 yr-1 Calculated c During monitoring

3.1.23 Leakage due to increased use of wood posts for fencing up to year t*

t CO2 Calculated c During monitoring

3.1.24 Perimeter of the areas to be fenced at year t

m Measurement m During monitoring

3.1.25 Average distance between wood posts

m Measurement m During monitoring

3.1.26 Fraction of posts from off-site non-renewable sources

Dimensionless Interview e During monitoring

3.1.27 Average volume of wood posts m3 Sampling e During monitoring


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9. Ex post net anthropogenic GHG removal by sinks

The net anthropogenic GHG removals by sinks is the actual net GHG removals by sinks minus the baseline net GHG removals by sinks minus leakage, therefore, following general formula can be used to calculate the net anthropogenic GHG removals by sinks of an A/R CDM project activity (CAR-CDM), in t CO2-e:

LKCCC BSLACTUALCDMAR −−=− (M.64)

where:

CAR-CDM Net anthropogenic greenhouse gas removals by sinks; t CO2-e

CACTUAL Actual net GHG removals by sinks; t CO2-e

CBSL Baseline net GHG removals by sinks; t CO2-e

LK Leakage, t CO2-e

Note: In this methodology Equation M.64 is used to estimate net anthropogenic GHG removals by sinks for the period of time elapsed between project start (t=1) and the year t=t*, t* being the year for which actual net greenhouse gas removals by sinks are estimated. This is done because project emissions and leakage are permanent, which requires to calculate their cumulative values since the starting date of the A/R CDM project activity.

Calculation of tCERs and lCERs

To estimate the amount of CERs that can be issued at time t*= t2 (the date of verification) for the monitoring period T = t2 – t1, this methodology uses the EB approved equations,39 which produce the same estimates as the following:

tCERs = CAR-CDM,t2 (M.65)

lCERs = CAR-CDM,t2 - CAR-CDM,t1 (M.66)

where:

tCERs Number of units of temporary Certified Emission Reductions

lCERs Number of units of long-term Certified Emission Reductions



10. Conservative Approach and Uncertainties

To help reduce uncertainties in accounting of emissions and removals, this methodology uses whenever possible the proven methods from the GPG-LULUCF, GPG-2000, and the IPCC’s Revised 2006 Guidelines. As well, tools and guidance from the CDM Executive Board on conservative estimation of emissions and removals are also used. Despite this, potential uncertainties still arise from the choice of parameters to be used. Uncertainties arising from, for example, biomass expansion factors (BEFs) or wood density, would result in uncertainties in the estimation of both baseline net GHG removals by sinks and the actual net GHG removals by sinks—especially when global default values are used. 39 See EB 22, Annex 15 <http://cdm.unfccc.int/EB/Meetings/022/eb22_repan15.pdf>.


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It is recommended that project participants identify key parameters that would significantly influence the accuracy of estimates. Local values that are specific to the project circumstances should then be obtained for these key parameters, whenever possible. These values should be based on:

• Data from well-referenced peer-reviewed literature or other well-established published sources;40

or

• National inventory data or default data from IPCC literature that has, whenever possible and necessary, been checked for consistency against available local data specific to the project circumstances; or

• In the absence of the above sources of information, expert opinion may be used to assist with data selection. Experts will often provide a range of data, as well as a most probable value for the data. The rationale for selecting a particular data value should be briefly noted in the CDM-AR-PDD. For any data provided by experts, the CDM—AR-PDD shall also record the experts name, affiliation, and principal qualification as an expert (e.g., that they are a member of a country's national forest inventory technical advisory group)—plus inclusion of a 1-page summary CV for each expert consulted, included in an annex.

In choosing key parameters or making important assumptions based on information that is not specific to the project circumstances, such as in use of default data, project participants should select values that will lead to an accurate estimation of net GHG removals by sinks, taking into account uncertainties. If uncertainty is significant, project participants should choose data such that it tends to under-estimate, rather than over-estimate, net GHG removals by sinks.

11. Uncertainties

(a) Uncertainties to be considered

The percentage uncertainty on the estimate of certain parameters and data (yield table values, biomass expansion factors, wood density, carbon fraction and other biophysical parameters) can be assessed from the sample standard deviation of measured sample values, using half the 95% confidence interval width divided by the estimated value, i.e.41,

( )100

%9521

(%) ⋅=µ

dthIntervalWiConfidenceUs (M.71)

( )100

421

⋅=µ

σ

where:

Us Percentage uncertainty on the estimate of the mean parameter value; %

µ Sample mean value of the parameter

σ Sample standard deviation of the parameter

40 Typically, citations for sources of data used should include: the report or paper title, publisher, page numbers,

publication date etc (or a detailed web address). If web-based reports are cited, hardcopies should be included as Annexes in the CDM-AR-PDD if there is any likelihood such reports may not be permanently available.

41 Box 5.2.1 in GPG LULUCF.


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If the default parameters are used, uncertainty will be higher than if locally measured parameters are used, and can be only roughly estimated with expert judgment42.

The percentage uncertainties on quantities that are the product of several terms are then estimated using the following equation43:

222

21 nS UUUU L++= (M.72)

where:

US Percentage uncertainty of product (emission by sources or removal by sinks)

Ui Percentage uncertainties associated with each term of the product (parameters and activity data), i=1,2,…,n

The percentage uncertainty on quantities that are the sum or difference of several terms can be estimated using following simple error propagation equation44:

snss

snsnssssc CCC

CUCUCUU

+++

⋅++⋅+⋅=

L

L

21

2222

211 )()()(

(M73)

where:

Uc Combined percentage uncertainty; %

Usi Percentage uncertainty on each term of the sum or difference; %

Csi Mean value of each term of the sum or difference

This methodology can basically reduce uncertainties through:

(i) Proper stratification of the project area into relatively homogenous strata;

Setting values for BEFs and root-shoot ratios.

11. Other information

This methodology is based on the approved methodology AR-AM0001. This methodology considers one additional source of leakage due to people displacement, and provides a procedure for making sure that other sources of leakage would not occur. This methodology not only accounts for living biomass, but also accounts for deadwood and litter. The baseline allows for land-use change.

12. References

All references are quoted in footnotes.

42 GPG LULUCF Chapter 5.2 and Chapter 3.2. 43 Equation 5.2.1 in GPG LULUCF. 44 Refers to Equation 5.2.2 in GPG LULUCF.


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Section IV: Lists of variables, acronyms and references

12. List of variables used in equations

Variable SI Unit Description N2Odirect-Nfertilizer, t t CO2-e yr-1 Increase in N2O emission in year t as a result of direct nitrogen

application within the project boundary µ Dimensionless Sample mean value of the parameter σ Dimensionless Sample standard deviation of the parameter ∆CAB, ijt t C yr-1 Changes in carbon stock in aboveground biomass of living trees for

stratum i, species j, time t ∆CAB,ijt t C yr-1 Changes in carbon stock in aboveground biomass of living trees for

stratum i, species j, time t ∆CBB, ijt t C yr-1 Changes in carbon stock in belowground biomass of living trees for

stratum i, species j, time t ∆CdescDW ijt t CO2-e yr-1 Annual decrease of carbon stock in the deadwood carbon pool due to

deadwood decomposition for stratum i, species j, time t ∆CdescLI ijt t CO2-e yr-1 Annual decrease of carbon stock in the litter carbon pool due to litter

decomposition for stratum i, species j, time t ∆CDW t CO2-e Sum of the changes in deadwood carbon stocks ∆CDW ijt t CO2-e yr-1 Annual carbon stock change in deadwood for stratum i, species j,

time t ∆CDWl,ijt t C yr-1 Annual carbon stock change in lying deadwood for stratum i,

species j, time t ∆CDWs,ijt t C yr-1 Annual carbon stock change in standing deadwood for stratum i,

species j, time t ∆CfwDW ijt t CO2-e yr-1 Annual decrease of carbon stock in the deadwood carbon pool due to

harvesting of deadwood for stratum i, species j, time t ∆CfwLI ijt t CO2-e yr-1 Annual decrease of carbon stock in the litter carbon pool due to

harvesting of litter for stratum i, species j, time t ∆CG, ijt t CO2-e yr-1 Annual increase in carbon stock due to biomass growth of trees for

stratum i, species j, time t ∆ChrDW ijt t CO2-e yr-1 Annual increase of carbon stock in the deadwood carbon pool due to

harvesting residues not collected for stratum i, species j, time t ∆ChrLI ijt t CO2-e yr-1 Annual increase of carbon stock in the litter carbon pool due to

harvesting residues not collected for stratum i, species j, time t ∆CL, ijt t CO2-e yr-1 Annual decrease in carbon stock due to biomass loss of trees for

stratum i, species j, time t ∆CLB t CO2-e Sum of the changes in living biomass carbon stocks of trees (above-

and below-ground) ∆CLB ijt t CO2-e yr-1 Verifiable changes in carbon stock in living biomass of trees for

stratum i, species j, time t ∆CLI t CO2-e Sum of the changes in litter carbon stocks ∆CLI ijt t CO2-e yr-1 Annual carbon stock change in litter for stratum i, species j, time t ∆CmlbDW ijt t CO2-e yr-1 Annual increase of carbon stock in the deadwood carbon pool due to

mortality of the living biomass for stratum i, species j, time t ∆CmlbLI ijt t CO2-e yr-1 Annual increase of carbon stock in the litter carbon pool due to

mortality of the living biomass for stratum i, species j, time t 0.001 Dimensionless Conversion kg to tonnes ERatN2O Dimensionless IPCC default emission ratio for N2O (0.007) ERatCH4 Dimensionless IPCC default emission ratio for CH4 (0.012) MWCH4-C t CH4 (t C)-1 Ratio of molecular weights of CH4 and C (16/12)


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Variable SI Unit Description GWPCH4 t CO2-e (t CH4)-1 Global Warming Potential for CH4 (21 for the first commitment

period) GWPN2O t CO2-e (t N2O)-1 Global Warming Potential for N2O (310 for the first commitment

period) MWCO2-C t CO2 (t C)-1 Ratio of molecular weights of CO2 and C (44/12) MWN2O-N t N2O (t N)-1 Ratio of molecular weights of N2O and N (44/28) A ha Total size of all strata, e.g. the total project area Aburn,i ha yr-1 Area of slash and burn for stratum i AD ha Area deforested by each displaced household ADh ha Area deforested by displaced household h Adistijt ha yr-1 Forest areas affected by disturbances in stratum i, species j, time t AditijT ha-1 yr-1 Average annual area affected by disturbances for stratum i, species j,

during the period T Ai ha Area of stratum i Ai ha

Size of each stratum (= ∑∑=

tcr

t

S

jijt

PS

A1

where tcr is the end of the

crediting period) Aijt ha Area of stratum i, species j, at time t AijT ha yr-1 Average annual area for stratum i, species j, during the period T Ait ha Area of stratum i, at time t Ai ha yr-1 Area of tree species i with fertilization AP ha Sample plot size APV m3 Average volume of wood posts (estimated from sampling) ASF ha Average size of small-holder farms in the larger project area BEF1,j Dimensionless Biomass expansion factor for conversion of annual net increment

(including bark) in merchantable volume to total above-ground biomass increment for species j

BEF2,,j Dimensionless Biomass expansion factor for converting merchantable volumes of extracted roundwood to total aboveground biomass (including bark) for species j

BEFj Dimensionless Biomass expansion factor for conversion of biomass of merchantable volume to above-ground biomass

Bi t d.m. ha-1 Average aboveground stock in living biomass before burning for stratum i

Bnon-tree i t d.m. ha-1 Average non-tree biomass stock on land to be planted before the start of a proposed A/R CDM project activity for stratum i

Bw, ijt t d.m. ha-1 Average above-ground biomass stock for stratum i, species j, time t CAB, ijt1 t C Carbon stock in aboveground biomass for stratum i, species j,

calculated at time t=t1 CAB, ijt2 t C Carbon stock in aboveground biomass for stratum i, species j,

calculated at time t=t2 CAB,ijt t C Carbon stock in aboveground biomass for stratum i, species j, at time t CACTUAL t CO2-e Actual net greenhouse gas removals by sinks CAR-CDM t CO2-e Net anthropogenic greenhouse gas removals by sinks CB(tv) t CO2 Estimated carbon stocks of the baseline scenario at time of

verification tv CBB, ijt1 t C Carbon stock in belowground biomass for stratum i, species j,

calculated at time t=t1 CBB, ijt2 t C Carbon stock in belowground biomass for stratum i, species j,

calculated at time t=t2 CBB,ijt t C Carbon stock in belowground biomass for stratum i, species j, at


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Variable SI Unit Description time t

CBSL t CO2-e yr-1 Baseline net GHG removals by sinks CDW ijt1 t C Total carbon stock in deadwood for stratum i, species j, calculated at

time t=t1 CDW ijt2 t C Total carbon stock in deadwood for stratum i, species j, calculated at

time t=t2 CDWij,t-1 t CO2-e Carbon stock in the deadwood carbon pool in stratum i, species j,

time t = t-1 year CDWl,ijt1 t C Carbon stock in lying deadwood for stratum i, species j, calculated at

time t=t1 CDWl,ijt2 t C Carbon stock in lying deadwood for stratum i, species j, calculated at

time t=t2 CDWs,ijt1 t C Carbon stock in standing deadwood for stratum i, species j, calculated

at time t=t1 CDWs,ijt2 t C Carbon stock in standing deadwood for stratum i, species j, calculated

at time t=t2 CE Dimensionless Combustion efficiency (IPCC default =0.5) CF t C (t d.m)-1 Carbon fraction (IPCC default value = 0.5) CFj t C (t d.m)-1 Carbon fraction of dry matter for species j CFLI it t C (t d.m)-1 Carbon fraction of litter from stratum i, time t as determined in

laboratory analysis if feasible (default value = 0.370) CFnon-tree t C (t d.m)-1 The carbon fraction of dry biomass in non-tree vegetation Ci e.g. US$ Cost of establishment of a sample plot for each stratum i CLB ijt1 t C Average annual carbon stock change in living biomass of trees CLI ijt1 t C Total carbon stock in litter for stratum i, species j, calculated at

time t=t1 CLI ijt2 t C Total carbon stock in litter for stratum i, species j, calculated at

time t=t2 CLI it2 t C Carbon stock in litter for stratum i, calculated at time t=t2 CP(tv) t CO2-e Existing carbon stocks at the time of verification tv Csi Dimensionless Mean value of each term of the sum or difference CSPdiesel Liter (l) yr-1 Volume of diesel consumption CSPdiesel,t Liter (l) yr-1 Amount of diesel consumption in year t CSPgasoline Liter (l) yr-1 Volume of gasoline consumption CSPgasoline,t l yr-1 Amount of gasoline consumption in year t D1, D2, …, Dn cm Diameter of pieces of deadwood in density state ds measured in plots

for stratum i, species j, time t DBHt cm Mean diameter at breast height at time t DBP m Average distance between wood posts dc 2, 3, or 4 Decomposition class DC Dimensionless Decomposition rate (% carbon stock in total deadwood stock

decomposed annually) DDWsdc t d.m. m-3

standing deadwood volume

Volume-weighted average deadwood density for decomposition class dc

Dj t d.m. m-3 Basic wood density for species j ds Dimensionless Deadwood density state (sound, intermediate, and rotten) Dwj t d.m. m-3

merchantable volume

Intermediate deadwood density for species j

E Dimensionless Allowable error E(t) t CO2-e Project emissions in year t


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Variable SI Unit Description EBiomassBurn, CH4 t CO2-e yr-1 CH4 emission from biomass burning in slash and burn EBiomassBurn, N2O t CO2-e yr-1 N2O emission from biomass burning in slash and burn EBiomassBurn,C t C yr-1 Loss of carbon stock in aboveground biomass due to slash and burn Ebiomassloss t CO2-e Decrease in the carbon stock in the tree and non-tree living biomass,

deadwood and litter carbon pools of pre-existing vegetation in the year of site preparation up to time t*

EF1 t N2O-N (t N input)-1

Emission factor for emissions from N inputs

EFdiesel kg CO2 l-1 Emission factor for diesel EFgasoline kg CO2 l-1 Emission factor for gasoline EFuelBurn t CO2-e yr-1 CO2 emissions from combustion of fossil fuels within the project

boundary EFuelBurn,t t CO2-e yr-1 Increase in GHG emission as a result of burning of fossil fuels within

the project boundary in year t EFxy Dimensionless CO2 emission factor for vehicle type x with fuel type y ENon-CO2, BiomassBurn t CO2-e yr-1 Non-CO2 emission as a result of biomass burning within the project

boundary ENon-CO2,BiomassBurn,t t CO2-e yr-1 Increase in Non-CO2 emission as a result of biomass burning within

the project boundary in year t exyt Liters km-1 Fuel consumption of vehicle type x with fuel type y at time t FGAR,t m3 yr-1 Volume of fuel-wood gathering allowed/planned in the project area

under the proposed A/R-CDM project activity FGBL m3 yr-1 Average pre-project annual volume of fuel-wood gathering in the

project area FGijt m3 yr-1 Annual volume of fuel wood harvesting of living trees for stratum i,

species j, time t FGijT m3 ha-1 yr-1 Average annual volume of fuel wood harvested for stratum i, species j,

during the period T FGoutside,t m3 yr-1 Volume of fuel-wood gathering displaced outside the project area at

year t FGt m3 yr-1 Volume of fuel-wood gathering displaced in unidentified areas FNRP Dimensionless Fraction of posts from off-site non-renewable sources fj(DBH,H) t d.m. ha-1 allometric equation for species j linking above-ground tree biomass

(kg tree-1) to diameter at breast height (DBH) and possibly tree height (H) measured in plots for stratum i, species j, time t

FON t N yr-1 Annual amount of organic fertilizer nitrogen applied adjusted for volatilization as NH3 and NOX

FracGASF t NH3-N and NOX-N (t N)-1

Fraction that volatilises as NH3 and NOX for synthetic fertilizers

FracGASM t NH3-N and NOX-N (t N)-1

Fraction that volatilises as NH3 and NOX for organic fertilizers

FS CO2-e ha-1 Mean carbon stock of forest vegetation in the larger project FSN t N yr-1 Amount of synthetic fertilizer nitrogen applied adjusted for

volatilization as NH3 and NOX FuelConsumptionxyt Liters Consumption of fuel type x of vehicle type y at time t Fwfijt Dimensionless Fraction of annually harvested deadwood carbon stock harvested as

fuel wood for stratum i, species j, time t GHGE t CO2-e yr-1 GHG emissions as a result of the implementation of the A/R CDM

project activity within the project boundary GHGE,t t CO2-e yr-1 Increase in GHG emission as a result of the implementation of the

proposed A/R CDM project activity within the project boundary in year t


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Variable SI Unit Description GTOTAL,ij t d.m ha-1 yr-1 Annual average increment rate in total biomass in units of dry matter

for stratum i, species j Gw,ij t d.m ha-1 yr-1 Average annual aboveground dry biomass increment of living trees for

stratum i species j h Dimensionless 1, 2, 3, ..., H, individual employments deemed likely to get lost Hfijt Dimensionless Fraction of annually harvested merchantable volume not extracted and

left on the ground as harvesting residue for stratum i, species j, time t Hijt m3 ha-1 yr-1 Annually extracted merchantable volume for stratum i, species j,

time t HijT m3 ha-1 yr-1 Average annual net increment in merchantable volume for stratum i,

species j during the period T Historical land use/cover data

Dimensionless Determining baseline approach

Ht m Mean tree height at time t i Dimensionless 1, 2, 3, … mPS ex post strata i Dimensionless 1, 2, 3, … mBL baseline strata Investment costs Dimensionless Including land purchase or rental, machinery, equipments, buildings,

fences, site and soil preparation, seedling, planting, weeding, pesticides, fertilization, supervision, training, technical consultation, etc. that occur in the establishment period

IRR, NPV, unit cost of service

Dimensionless Indicators of investment analysis

Iv,ij m3 ha-1 yr-1 Average annual increment in merchantable volume for stratum i species j

Iv,ijT m3 ha-1 yr-1 Average annual net increment in merchantable volume for stratum i, species j during the period T

j Dimensionless 1, 2, 3, … sPS planted tree species j Dimensionless 1, 2, 3, … sBL baseline tree species kxyt km Kilometers traveled by each of vehicle type y with fuel type x at time t LT 100 m Transect length Land use/cover map Dimensionless Demonstrating eligibility of land, stratifying land area Landform map Dimensionless Stratifying land area l-CER(tv) t CO2-e l-CERs emitted at time of verification tv LE(t) t CO2-e Leakage: estimated emissions by sources outside the project boundary

in year t Lfw, ijt CO2-e yr-1 Annual carbon loss due to fuel wood gathering for stratum stratum i,

species j, time t Lhr, ijt t CO2-e yr-1 Annual carbon loss due to commercial harvesting for stratum i,

species j, time t LK t CO2-e Leakage LKconversion t CO2-e Leakage due to conversion of land to grazing land LKfencing t CO2-e Leakage due to increased use of wood posts for fencing up to year t*;

t CO2-e LK fuel-wood t CO2-e Leakage due to displacement of fuel-wood collection up to year t*;

t CO2-e LKPeopleDiscplacement t CO2-e Total leakage due to deforestation due to people displacement LKVehicle t CO2-e yr-1 Total GHG emissions due to fossil fuel combustion from vehicles LKVehicle,CO2 t CO2-e yr-1 Total CO2 emissions due to fossil fuel combustion from vehicles Lot, ijt CO2-e yr-1 Annual natural losses (mortality) of carbon for stratum i, species j,

time t LP_B(tv) t CO2-e Leakage: estimated carbon pools outside the project boundaries in the

baseline scenario on areas that will be affected due to the


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Variable SI Unit Description implementation of a project activity at time of verification tv

LP_P(t) t CO2-e Leakage: existing carbon pools outside the project boundaries that have been affected by the implementation of a project activity at time of verification tv

MCAB, ijt t C ha-1 Mean carbon stock in above-ground biomass per unit area for stratum i, species j, time t

MCBB, ijt t C ha-1 Mean carbon stock in below-ground biomass per unit area for stratum i, species j, time t

MCDWlijt t C ha-1 Mean carbon stock in lying deadwood per unit area for stratum i, species j, time t

MCDWsijj,dc t C ha-1 Mean carbon stock in standing deadwood per unit area for stratum i, species j, time t

MCDWsijt t C ha-1 Mean carbon stock in standing deadwood per unit area for stratum i, species j, time t

MCLI it t C ha-1 Mean carbon stock in litter per unit area for stratum i, time t MfijT Dimensionless Mortality factor = fraction of Vijt1 died during the period T Mfijt Dimensionless Mortality factor = fraction of Vijt dying at time t MVDWlijt,ds m3 ha-1 Mean volume of lying deadwood per area unit in density state ds for

stratum i, species j, time t MVDWsijt m3 ha-1 Mean volume of dead standing deadwood per unit area for stratum i,

species j, time t in decomposition class dc MVijt m3 ha-1 Mean merchantable volume per unit area for stratum i, species j, time t MWLI it t ha-1 Mean weight of litter per unit area for stratum i, time t n Dimensionless Sample size (total number of sample plots required) in the project area ni Dimensionless Sample size for stratum i N Dimensionless Maximum possible number of sample plots in the project area Ni Dimensionless Maximum possible number of sample plots in stratum i N/C ratio t N (t C)-1 Nitrogen-carbon ratio National and sectoral policies

Dimensionless Additionality consideration

NDH Dimensionless Number of employees that lose their employment due to the project activity

nh. Dimensionless Number of samples per stratum that is allocated proportional to

hhh CsW ⋅

NON-Fert t N yr-1 Mass of organic fertilizer nitrogen applied NON-Fert,t t N yr-1 Total use of organic fertiliser within the project boundary in year t NSN-Fert t N yr-1 Amount of organic fertilizer nitrogen applied NSN-Fert t N yr-1 Mass of synthetic fertilizer nitrogen applied NSN-Fert,t t N yr-1 Total use of synthetic fertiliser within the project boundary in year t nTRijt ha-1 Number of trees in stratum i, species j, at time t nxyt Dimensionless Number of vehicles nxyt Dimensionless Number of vehicles Operations and maintenance costs

Dimensionless Including costs of thinning, pruning, harvesting, replanting, fuel, transportation, repairs, fire and disease control, patrolling, administration, etc.

p Dimensionless Desired level of precision (e.g. 10%) pl Dimensionless Plot number in stratum i, species j PLij Dimensionless Total number of plots in stratum i, species j Q e.g. m3 ha-1 Approximate average value of the estimated quantity Q, (e.g. wood

volume) Revenues Dimensionless Revenues from timber, fuel-wood, non-wood products, with and


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Variable SI Unit Description without CER revenues, etc.

Rj Dimensionless Root-shoot ratio Satellite image Dimensionless Demonstrating eligibility of land, stratifying land area sti Dimensionless Standard deviation for each stratum i Soil map Dimensionless Stratifying land area SFGBL m3 yr-1 Sampled average pre-project annual volume of fuel-wood gathering in

the project area SFRPAfw Dimensionless Fraction of total area or households in the project area sampled t Years 1, 2, 3, …t* years elapsed since the start of the A/R CDM project

activity T Years Number of years between monitoring time t2 and t1 (T=t2-t1) T Years Number of years between two monitoring events which in this

methodology is 5 years T Years Number of years between times t2 and t1 (T = t2-t1) TBABj kg tree-1 Above-ground biomass of a tree TCAB kg C tree-1 Carbon stock in above-ground biomass per tree TCBB kg C tree-1 Carbon stock in below-ground biomass per tree PARt m Perimeter of the areas to be fenced at year t t-CER(tv) t CO2-e t-CERs emitted at time of verification tv tr Dimensionless Tree (TR = total number of trees in the plot) Transaction costs Dimensionless Including costs of project preparation, validation, registration,

monitoring, etc. tv Year Year of verification Uc % Combined percentage uncertainty Ui i=1,2,…,n Percentage uncertainties associated with each term of the product

(parameters and activity data) Us % Percentage uncertainty on the estimate of the mean parameter value US % Percentage uncertainty of product (emission by sources or removal by

sinks) Usi % Percentage uncertainty on each term of the sum or difference Vijt m3 ha-1 Average merchantable volume of stratum i, species j, at time t Vijt1 m3 ha-1 Average merchantable volume of stratum i, species j, at time t = t1 Vijt2 m3 ha-1 Average merchantable volume of stratum i, species j, at time t = t2 x Dimensionless Vehicle type XF Dimensionless Plot expansion factor from per plot values to per hectare values y Dimensionless Fuel type zα/2 Dimensionless Value of the statistic z (normal probability density function), for

α = 0.05 (implying a 95% confidence level) ∆MCAB,ijt t C ha-1 yr-1 Mean change in above-ground carbon stock in stratum i, species j, at

time t ∆MCABij t C ha-1 Mean change in above-ground carbon stock in stratum i, species j,

between two monitoring events ∆MCBB,ijt t C ha-1 yr-1 Mean change in below-ground carbon stock in stratum i, species j, at

time t ∆MCBBij t C ha-1 Mean change in below-ground carbon stock in stratum i, species j,

between two monitoring events ∆PCAB t C ha-1 Plot level change in above-ground mean carbon stock between two

monitoring events ∆PCABij,pl t C ha-1 Plot level change in above-ground mean carbon stock in stratum i,

species j, between two monitoring events ∆PCBB t C ha-1 Plot level change in below-ground mean carbon stock between two

monitoring events


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Variable SI Unit Description ∆PCBBij,pl t C ha-1 Plot level change in below-ground mean carbon stock in stratum i,

species j, between two monitoring events ∆TCAB kg C tree-1 Change in above-ground biomass carbon per tree between two

monitoring events κ Year Time span between two verification occasions

13. List of acronyms used in the methodologies

Acronym Description A/R Afforestation and Reforestation EB The Executive Board of the CDM BEF Biomass Expansion Factor (for converting from commercial volume to total tree biomass) CDM Clean Development Mechanism CER Certified Emission Reduction CF Carbon Fraction CP Conference of Parties to UNFCCC DBH Diameter at Breast Height DNA Designated National Authority GIS Geographic Information System GHG Greenhouse Gases GPG Good Practice Guidance GWP Global Warming Potential H Tree Height IPCC Intergovernmental Panel on Climate Change lCER long-term Certified Emission Reduction LULUCF Land Use Land-Use Change and Forestry NFS Nitrogen Fixing Species PDD Project Design Document QA Quality Assurance QC Quality Control RS Root to shoot ratio tCER temporary Certified Emission Reduction

14. References:

All references are quoted in footnotes.

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History of the document

Version Date Nature of revision 03 EB 42, Annex 11

26 September 2008 Allowing displacement of grazing activities, improvement of land use change approach, many editorial changes.

02 EB 36, Para 39 30 November 2007

Clarification to the application of the definition of the project boundary in A/R CDM project activities.

01 EB 29, Annex 7 16 February 2007

Initial adoption.

Documents

Approved afforestation and reforestation baseline and ... · reforestation project activities under the control of the project participants. UNFCCC/CCNUCC CDM – Executive Board